Startseite Key Frame Extraction of Multi-Resolution Remote Sensing Images Under Quality Constraint
Artikel Open Access

Key Frame Extraction of Multi-Resolution Remote Sensing Images Under Quality Constraint

  • Yijun Liu , Ziwen Zhang EMAIL logo und Feng Li
Veröffentlicht/Copyright: 31. Dezember 2019
Artikel downloaden (PDF)
Open Physics
Aus der Zeitschrift Open Physics Band 17 Heft 1

Abstract

In key frame extraction of multi-resolution remote sensing image using traditional key frame image feature extraction method, only the feature information of remote sensing images, rather than cluster operation of the remote sensing images is considered, which leads to low efficiency and poor quality of extraction results. To this end, the key frame extraction algorithm of multi-resolution remote sensing image under quality constraint was proposed. Through similarity between image features and the selected image frame, rough key frame can be extracted. On this basis, the key frame extraction of multi resolution remote sensing image based on quality constraints was used to perform clustering operation for multi-resolution remote sensing image corresponding to rough key frame, which shortened the time length for retrieval of key frame image. According to the clustering results, multi-resolution remote sensing images were divided into several clusters. The key frame of each cluster can be obtained by calculating the distance between remote sensing image and cluster center. For key frames that had been determined, their quality was evaluated to meet standard, so as to realize effective extraction of key frame of multi-resolution remote sensing images. The experimental results show that the proposed method can significantly improve the quality of key frame extraction of multi-resolution remote sensing images.

Keywords: quality constraint; multi resolution; remote sensing image; key frame; extraction; clustering operation
PACS: 42.68.Wt; 68.43.Hn

1 Introduction

Remote sensing image is the main form of information media in the field of information processing. Most of the acquired remote sensing images are disordered images, which have the characteristics of large number, large information redundancy and uneven quality. Therefore, the problem of information processing is no longer the lack of content of remote sensing images, but how to effectively extract the required data according to the data characteristics of digital images, which is the key frame extraction technology. Key frame is also called representative frame, which represents one or more images of the main content of digital image. Under the quality constraints, key frame extraction of disordered multi-resolution remote sensing image can greatly reduce the amount of data processing.

Remote sensing image is an important representation of information in geoprocessing. Most of remote sensing images obtained by satellite are multi-resolution images, which have large data size, insignificant feature information, poor image quality. Therefore, it has become one of hot issues to extract key frames of multi-resolution remote sensing images. In traditional image feature-based key frame extraction method, only the feature information of image rather than clustering operation should be considered, which may lead to low efficiency and poor quality of extracted key frames [1]. To solve such problem, this paper proposes a key frame extraction method of multi-resolution remote sensing image under quality constraints, which can significantly improve the efficiency and quality in key frame extraction of multi-resolution remote sensing images.

2 Key Frame Extraction of Multi-Resolution Remote Sensing Image Based on Quality Constraints

2.1 Key frame extraction algorithm based on image feature

Key frames refer to the multi-resolution images which have special feature and need to be immediately extracted in remote sensing images obtained by satellite. The content of this type of images can represent the key contents of remote sensing image obtained by satellite. However, there is a variety of remote sensing images having special feature [2]. Therefore, it is necessary to quickly extract key frames from enormous amount of multi-resolution remote sensing images and enhance the retrieval rate of multi-resolution remote sensing images.

Based on the features of selected multi-resolution remote sensing images, the similarity between image feature and selected image frame was calculated according to equation (1):

(1) l i = ∑ i = 1 n ( f i , … f 0 ) 2 / ( n 2 )

In Formula (1), n represents the upper limit of the number of key frames extracted from the resolution remote sensing image, and fi represents the number of key frames extracted from the resolution remote sensing image.

Extracting key features from image base according to equation (2):

(2) P i = t 0 ( t 1 … … t n ) / n

Calculating the similarities among key features of multi-resolution remote sensing images according to equation (3)

(3) S = 1 ( t 1 − p 1 ) 2 w 1 + ( t 2 − p 2 ) 2 w i + … … ( t 14 − p 14 ) 2 w 14

In equation (1), ti represents a certain feature vector of a certain key frame multi-resolution remote sensing image [3]; in equation (2), pi is the feature vector exclusively owned by key frame, and the difference between ti and pi indicates a certain change of a key frame image; in equation (3), wi represents the weight of a multi-resolution remote sensing image. The comparison of similarity is performed according to a preset threshold value, if the threshold value is met, the remote sensing image is the key frame, otherwise it is not the key frame.

It can be known from above analyses that to obtain accurate key frame of feature image, the key is to have the exclusively-owned feature vector which significantly differs from other feature vectors, i.e. when the difference between ti and pi is large, the calculation results based on equation (3) are more accurate [3]. In normal situations, the feature information contained in multi-resolution remote sensing images obtained by satellite contain are similar to each other, it is impossible to recognize and obtain accurate key frame using subtraction of feature vectors. To solve such problem, a key frame extraction algorithm of multi-resolution remote sensing images based on quality constraints was proposed in this study.

2.2 Key frame extraction algorithm of multi-resolution remote sensing images based on quality constraints

Clustering operation for the multi-resolution remote sensing image corresponding to rough key frame was performed. N multi-resolution remote sensing images were divided into severe clusters according to clustering operation results [4]; The clustering center of each cluster was calculated, and the image which is closest to the clustering center was selected as the key frame; The quality of key frame of each cluster was evaluated. Figure 1 shows the extraction flow of key frame.

Figure 1 The extraction flow of key frame
Figure 1

The extraction flow of key frame

For extraction of key frame of multi-resolution remote sensing images, technical support and algorithms are required, which is beneficial for extracting key frames from massive amount of multi-resolution remote sensing images [5]. Data clustering technique has been used for large data-sized image base for classification of image feature and improvement of key frame extraction rate

A preset K value is required for K-means clustering algorithm, i.e. selecting k images from all multi-resolution remote sensing images as clustering center, then an image is selected from the remaining images, and the similarity distances between such image can k clustering centers are calculated. The cluster which has the smallest distance is selected as belonging cluster. It is worth noting that for every one multi-resolution image is increased in k clusters, the similarity distance between image and clustering center should be recalculated.

In this study, the k value is automatically determined according to the image content contained in multi-resolution remote sensing image [6]. The concrete process is described as follow. Each multi-resolution remote sensing image is segmented into M blocks, M=6, then the mean and variance of textural feature of segmented image are set to m l  and e l 2 , which can be expressed by equation (4) and (5), respectively:

(4) m l = E ( X l ) = 1 D 2 ∑ i = 0 D − 1 ∑ j = 0 D − 1 x l ( i , j ) , l = 1 , 2 , … , M
(5) e l 2 = E ( X l − E ( X l ) ) 2 = 1 D 2 ∑ i = 0 D − 1 ∑ j = 0 D − 1 x l ( i , j ) − E ( X l ) 2 , l = 1 , 2 , … M

In equation (4) and (5), D represents the row number and column number of blocks of segmented image, 1 represents the No. of block, xl(i, j) represents the pixel of block

The means and variances of M image blocks are selected as the feature vectors of a complete multi-resolution remote sensing image:

(6) F = m 1 , e 1 2 , m 2 , e 2 2 , … , m M , e M 2

Normalized operation of feature vectors is conducted [7]. Suppose the original vector expression is [f1, f2, . . . , fM],fi = mi, the equation of normalized operation is shown as (7):

(7) F i = f i − m e , i = 1 , 2 , … M

e and m represent the standard deviation and mean of original feature vector in equation (7), respectively. After normalization process, the feature vector can be expressed as [F1, F2, . . . , FM]. In this study, two of multi-resolution remote sensing images will be selected, of which the feature vector expressions after normalization are [Fa1, Fa2, . . . , FaM] and [Fb1, Fb2, . . . , FbM], the similarity distance between two images can be calculated by equation (8).

(8) d i s t ( F a , F b ) = ∑ i = 1 M ( F a i − F b i ) 2 1 2

The calculation equation for the mean value of the sum of similarity distances between two random remote sensing images is shown as equation (9), T is the threshold value [8].

(9) T = 1 N × ( N − 1 ) ∑ i ≠ j N d i s t ( F i , F j )

In equation (9), N represents the total number of multi-resolution remote sensing images, the similarity in content between two remote sensing images is evaluated by similarity distance [9], if the similarity distance is smaller than T value, indicating the two images belong to the same cluster, vice versa.

The K-means clustering operation proposed in this study is described as follow

  1. The first multi-resolution remote sensing image F1 is put in the cluster k1 , and such image is regarded as the clustering center.

  2. For the next remote sensing image F i, the value of i varies between 2 and N, N represents the number of multi-resolution remote sensing images

  3. The Cluster Kj(j = 1, 2, . . . Nc) obtained based on dist d i s t ( F a , F b ) = ∑ i = 1 M ( F a i − F b i ) 2 1 2 has similarity distance as dist(Fi, Kjc), Kjc represents the clustering center of cluster K j, the shortest similarity distance between K jc and Ki is calculated, if the result is no more than threshold T, then such remote sensing image belongs to cluster K j, and the new clustering center is calculated [10].

  4. If the shortest similarity distance between Kjc and Ki is larger than threshold T, indicating such image has already existed in any of clusters, with no similarity, and such multi-resolution remote sensing image should be classified into another new cluster.

  5. According to step (2) to (4), clustering operations of all multi-resolution remote sensing images are performed [11] to classify the images into different clusters Kj(j = 1, 2, . . . Nc).

    Through clustering operation, N multi-resolution remote sensing images can be segmented into different clusters. In each cluster, the remote sensing image which is closest to clustering center is selected as key frame. The sum of key frames of all clusters constitute the key frame of all remote sensing image.

2.3 Evaluation of quality of key frame extraction

The evaluation process of quality of key frame of multi-resolution remote sensing image is describe as follow:

  1. Fuzzy processing of multi-resolution remote sensing image F k is performed to obtained fuzzy imageb:

(10) b v = h v × F k b H = h h × F k h v = 1 9 × 111111111 h h = ( h v ) T = h v

Where bv and bH represent the low-pass filter processed image of multi-resolution remote sensing image F k in vertical and horizontal direction, respectively; h h and hv represent the vertical and horizontal model of filter, respectively [12].

  1. Before filter processing of multi-resolution remote sensing image F k, the errors of adjacent pixels in vertical and horizontal direction are calculated, which are expressed by Dfv(i, j) and DfH(i, j), respectively. The errors of adjacent pixels of Fig.b (obtained by fuzzy processing)in vertical and horizontal direction are Dbv(i, j) and DbH(i, j), the calculation equation for the variation of difference value between two adjacent pixels is shown as below:

(11) D F V ( i , j ) = ( F k ( i , j ) − F k ( i − 1 , j ) ) D F H ( i , j ) = ( F k ( i , j ) − F k ( i . j − 1 ) D b v ( i . j ) = ( b V ( i , j ) − b V ( i − 1 , j ) D b H ( i , j ) = ( b H ( i , j − 1 )

  1. Both step (1) and (2) describe the calculation of pixel [13]. To obtain all the differences in one remote sensing image, the sum of all differences between adjacent pixels in the image must be calculated.

(12) s f V = ∑ i , j = 1 m − 1 , n − 1 D F V ( i , j ) s f H = ∑ i , j = 1 m − 1 , n − 1 D F H ( i , j ) s b V = ∑ i , j = 1 m − 1 , n − 1 D b V ( i , j ) s b H = ∑ i , j = 1 m − 1 , n − 1 D b H ( i , j )

Through normalized processing, we can obtain

(13) b F V = s F V − s b V s F V b F H = s F H − s b H s F H C l e a r = max ( b F V , b F H )

The Clear value is the quality evaluation results of key frame extraction of multi-resolution remote sensing image [14], which varies between 0 and 1. The larger the Clear value is, the more clear the extracted key frame image is, vice versa. If the key frame results of extracted multi-resolution remote sensing image meet the requirements, then the extracted results can be regarded as key frame; otherwise, return to cluster for re-extraction of key frame [15]. The process continuously proceed until the extracted key frame meets the quality requirement.

3 Experimental Analysis

The effectiveness of proposed method was experimentally validated. In this experiment, data collected in gagamatch platform (www.gagamatch.com), 30 multi-resolution remote sensing images were collected from 5 different scenes (6 images for each scene). The multi-resolution remote sensing images, all of which are 640*480 in pixel, were segmented into 16 blocks, from each block 16 feature vectors were extracted. Table 1 shows the calculation results of feature vectors of 30 multi-resolution remote sensing images by proposed method [16, 17, 18, 19]. The threshold T value of 30 remote sensing images calculated by equation (9) is 46.5.

Table 1

Feature vectors of multi-resolution remote sensing images

No. Remote sensing image 1 Remote sensing image 2 Remote sensing image 3 Remote sensing image 4 ...... Remote sensing image 28 Remote sensing image 29 Remote sensing image 30
1 50.5 24.8 33.2 17.32 ...... 33.9 17.29 38.04
2 50.9 23.4 34.1 17.27 ...... 34.2 17.2 38.01
3 48.7 23.8 33.7 16.68 ...... 34.6 16.13 38.62
4 49 24.3 33.4 16.17 ...... 33.8 17 38.14
5 52.3 24.6 33.6 17.02 ...... 33.6 16.35 39.62
6 50.8 22.7 33.8 16.66 ...... 34.4 17.61 38.65
7 50.2 22.8 33.5 15.69 ...... 34.5 16.41 40.21
8 49.1 24.3 33.4 15.33 ...... 33.7 17.77 38.08
9 50.7 24.2 33.4 16.52 ...... 34.1 18.27 40.48
10 50.7 23.9 33.4 16.86 ...... 33.9 15.64 40.87
11 50.5 24 33.1 16.42 ...... 34.5 18.65 41.84
12 50.4 24.1 34.3 15.41 ...... 33.2 17.15 41.06
13 50.3 24.7 34.5 17.14 ...... 33.7 16.99 40.84
14 50 24.6 33.7 17.28 ...... 34.3 16.67 40.94
15 50.8 24 33.4 17.58 ...... 34.2 15.91 41.33
16 50.5 24.4 33.6 17.18 ...... 33.6 16.21 40.2
Mean value of feature vectors 50.3 24 33.6 16.66 ...... 34 16.95 39.8

According to Table 1, it can be known that the difference in feature vector of 16 segmented blocks is small, the error range is within 0-0.5; The simultaneous comparison of 30 selected 30 remote sensing images shows that the feature vectors of remote sensing images collected from the same environment are similar to each other, while the feature vectors of multi-resolution remote sensing images collected from different environments are significantly different [20]. Therefore, it can be concluded that the difference in similarity distance of multi-resolution remote sensing images collected from the same environment is small, and far smaller than the threshold value; in contrast, the difference in similarity distance of multi-resolution remote sensing images collected from different environments is large, and far larger than the threshold value [21].

The proposed method was used for clustering processing of remote sensing images selected in experiment. If the similarity distance of multi-resolution remote sensing images collected from different environments is smaller than threshold value, the remote sensing images are classified into the same cluster, otherwise a new cluster should be established.

The key frames of remote sensing images that have been classified were extracted, and the image which is closest to clustering center is selected as key frame. Figure 2 shows key frames extracted from different clusters. The evaluation results of key frame quality are shown in Table 2.

Figure 2 Extraction results of key frames
Figure 2

Extraction results of key frames

Table 2

Evaluation results of key frame quality

Evaluation angle Key frame1 Key frame 2 Key frame 3 Key frame 4 Key frame 5
Vertical direction 0.44 0.28 0.46 0.48 0.41
Horizontal direction 0.48 0.18 0.42 0.51 0.42
Clear 0.48 0.28 0.46 0.51 0.42

In evaluation of quality of key frame extracted from multi-resolution remote sensing images using proposed method, an objective and realistic evaluation criterion should be adopted to validate the effectiveness of proposed method. In this experiment, INRIA Holidays dataset provided by VGG group of Oxford University was selected as research objects. 10 images were randomly selected from such dataset, and the quality evaluation value of each image was calculated. Figure 3 shows the 10 test images. Table 3 lists the quality evaluation results of test images.

Figure 3 10 test images
Figure 3

10 test images

Table 3

Quality evaluation results of test images

Evaluation angel of test image Key frame 1 Key frame 2 ... Key frame 9 Key frame 10
Vertical direction 0.40 0.59 ... 0.53 0.49
Horizontal direction 0.43 0.41 ... 0.42 0.44
Clear 0.43 0.59 ... 0.53 0.49

According to Table 3, the mean value of quality evaluation results of 10 images is 0.50. If using such value as the evaluation standard for ordinary image, there will be no images meeting the standard. Therefore, the value of 0.35 was adopted as the evaluation standard of extracted key frame quality. If the quality evaluation result of multi-resolution remote sensing image is less than 0.35, the extracted key frame will be deleted and re-extracted for quality evaluation, until the extracted value of key frame is no less than 0.35.

As shown in Table 2, the quality evaluation results of key frame 2 is 0.27, which is lower than standard value 0.35. Moreover, the image background of key frame 2 is fuzzy and the overall quality of image is poor, which cannot meet the requirement. Therefore, we returned to the cluster 2 where the key frame 2 belongs, and re-extracted a new key frame. The evaluation results of re-extracted key frame are shown in Figure 4. The quality evaluation results of re-extracted remote sensing image are shown in Table 4.

Figure 4 Re-extraction results of key frame
Figure 4

Re-extraction results of key frame

Table 4

The quality evaluation results of re-extracted key frame

Evaluation angle of test image Key frame 1 Key frame 2 Key frame 3 Key frame 4 Key frame 5
Vertical direction 0.42 0.51 0.47 0.46 0.39
Horizontal direction 0.46 0.35 0.38 0.49 0.40
Clear 0.46 0.51 0.47 0.49 0.40

From Table 4, the quality evaluation result of key frame re-extracted from multi-resolution remote sensing image meet the standard and the requirement of quality constraints. This indicates that the proposed method is effective in extracting key frame from multi-resolution remote sensing images under quality constraints.

4 Conclusion

In view of the characteristics of traditional multi-resolution remote sensing image key frame extraction technology, such as large number of extraction, large information redundancy and uneven quality, a key frame extraction method of multi-resolution remote sensing image based on quality constraints is proposed. For the multi-resolution remote sensing image of coarse key frame, clustering operation can shorten the time length of key frame image retrieval. According to the clustering results, multi-resolution remote sensing images are divided into several categories. By calculating the distance between remote sensing image and cluster center, the key frame of each cluster is obtained. The quality of the key frame is evaluated to reach the standard, and the key frame of multi-resolution remote sensing image is extracted effectively. The experimental results show that this method can significantly improve the quality of key frame extraction of remote sensing image, and get the key frame satisfying the quality requirements. In the future, how to reduce the key frame extraction time of multi-resolution remote sensing image can be further studied.

Acknowledgement

The paper is supported by funds from Department of Science and Technology of Guangdong Province (No. 2018B030338001, No. 2018B010107003) and a fund from PengCheng Laboratory.

References

[1] Zheng E., Lin J.Y., Key frame extraction from disordered image based on image quality constraints, Computer Engineering, 2017, 43(11), 210-215.Suche in Google Scholar

[2] Tan H.P., Zeng X.J., Niu S.J., et al., Multi-scale defuzzification of remote sensing image based on regularized constraints, Journal of Image and Graphics, 2015, 20(3), 386-394.Suche in Google Scholar

[3] Lin X., Luo X.J., Guo H.M., et al., Extraction method of GF-1 remote sensing image at mountainous area based on semantic constraints, Journal of Mountain Science, 2017, 35(1), 102-111.Suche in Google Scholar

[4] Wang L.Z., Lin X.G., Liang Y., Perceptual organization method for main route extraction of high-resolution remote sensing image, Science of Surveying and Mapping, 2017, 42(7), 127-131.Suche in Google Scholar

[5] Hu R.M., Huang X.B., Huang Y.C., Building extraction of high-resolution remote sensing image by enhancing the morphological index of buildings, Acta Geodaetica et Cartographica Sinica, 2014, 43(5), 514-520.10.1080/2150704X.2014.963732Suche in Google Scholar

[6] Gao W., Wang K., Yuan F.J., et al., Building extraction of high-resolution remote sensing image based on invariant moment, Application Research of Computers, 2014, 31(2), 622-624.Suche in Google Scholar

[7] Xie G.X., Huang W.X., Lu Y., et al., Research on mulberry information extraction based on high-resolution remote sensing image —Case study of Luzhai County of Guangxi province, Chinese Journal of Agricultural Resources and Regional Planning, 2015, 36(2), 44-53.Suche in Google Scholar

[8] Chen J., Chen T.Q., Liu H.M., et al., Layered extraction of cultivated land of high-resolution remote sensing image, Transactions of CSAE, 2015, 31(3), 190-198.Suche in Google Scholar

[9] Zhang N., Zhang X.L., Ye L., Crown extraction of high-resolution remote sensing image based on improved peak climbing method, Transactions of the Chinese Society for Agricultural Machinery, 2014, 45(12), 294-300.Suche in Google Scholar

[10] Guo Y.S., Liu Q.S., Liu G.H., et al., Sing tree crown extraction of high-resolution remote sensing image based on marker control based watershed segmented method, Geo-information Science, 2016, 18(9), 1259-1266.Suche in Google Scholar

[11] Chen H., Tao C., Zou Z.R., et al., Residential area extraction of high-resolution remote sensing image using marginal density feature, Journal of Applied Science, 2014, 32(5), 537-542.Suche in Google Scholar

[12] Wu W., Ding X.Q., Yan M., Multidate high-resolution remote sensing image registration based on anomaly area perception, Journal of Computer Applications, 2016, 36(10), 2870-2874.Suche in Google Scholar

[13] Hu H.L., Wu B., Qin Z.Y., et al., Forest land boundary extraction of high-resolution remote sensing image, Journal of Geomatics Science and Technology, 2016, 33(4), 394-399.Suche in Google Scholar

[14] Zhou S.G., Sun J.Y., Fan L., et al., Building profile extraction of high-resolution remote sensing image, Remote Sensing for Land & Resources, 2015, 27(3), 52-58.Suche in Google Scholar

[15] Li S.S., Chen Y., Zhang C., et al., Evaluation model for land reclamation project progress based on multidate high-resolution remote sensing image, China Land Science, 2014, 28(3), 83-88.Suche in Google Scholar

[16] Devaki P., Sreenadh S., Vajravelu K., Prasad K. V., Vaidya H., Wall properties and slip consequences on peristaltic transport of a casson liquid in a flexible channel with heat transfer, Applied Mathematics & Nonlinear Sciences, 2018, 3, 277-290.10.21042/AMNS.2018.1.00021Suche in Google Scholar

[17] Gao W., Wang W.F., The fifth geometric-arithmetic index of bridge graph and carbon nanocones, Journal of Difference Equations and Applications, 2017, 23, 100-109.10.1080/10236198.2016.1197214Suche in Google Scholar

[18] Malviya P.S., Yadav N., Ghosh S., Acousto-optic modulation in ion implanted semiconductor plasmas having SDDC, Applied Mathematics & Nonlinear Sciences, 2018, 3, 303-310.10.21042/AMNS.2018.1.00023Suche in Google Scholar

[19] Mi C., Shen Y., Mi W.J., Huang Y.F., Ship identification algorithm based on 3D point cloud for automated ship loaders, Journal of Coastal Research, 2015, 73, 28-34.10.2112/SI73-006.1Suche in Google Scholar

[20] Pandey P.K., Jaboob S.S. A., A finite difference method for a numerical solution of elliptic boundary value problems, Applied Mathematics & Nonlinear Sciences, 2018, 3, 311-320.10.21042/AMNS.2018.1.00024Suche in Google Scholar

[21] Vajravelu K., Li R., Dewasurendra M., Benarroch J., Ossi N., Zhang Y., Sammarco M., Prasad K. V., Effects of second-order slip and drag reduction in boundary layer flows, Applied Mathematics & Nonlinear Sciences, 2018, 3, 291-302.10.21042/AMNS.2018.1.00022Suche in Google Scholar
Received: 2019-11-04
Accepted: 2019-12-03
Published Online: 2019-12-31

© 2019 Y. Liu et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

Artikel in diesem Heft

  1. Regular Articles
  2. Non-equilibrium Phase Transitions in 2D Small-World Networks: Competing Dynamics
  3. Harmonic waves solution in dual-phase-lag magneto-thermoelasticity
  4. Multiplicative topological indices of honeycomb derived networks
  5. Zagreb Polynomials and redefined Zagreb indices of nanostar dendrimers
  6. Solar concentrators manufacture and automation
  7. Idea of multi cohesive areas - foundation, current status and perspective
  8. Derivation method of numerous dynamics in the Special Theory of Relativity
  9. An application of Nwogu’s Boussinesq model to analyze the head-on collision process between hydroelastic solitary waves
  10. Competing Risks Model with Partially Step-Stress Accelerate Life Tests in Analyses Lifetime Chen Data under Type-II Censoring Scheme
  11. Group velocity mismatch at ultrashort electromagnetic pulse propagation in nonlinear metamaterials
  12. Investigating the impact of dissolved natural gas on the flow characteristics of multicomponent fluid in pipelines
  13. Analysis of impact load on tubing and shock absorption during perforating
  14. Energy characteristics of a nonlinear layer at resonant frequencies of wave scattering and generation
  15. Ion charge separation with new generation of nuclear emulsion films
  16. On the influence of water on fragmentation of the amino acid L-threonine
  17. Formulation of heat conduction and thermal conductivity of metals
  18. Displacement Reliability Analysis of Submerged Multi-body Structure’s Floating Body for Connection Gaps
  19. Deposits of iron oxides in the human globus pallidus
  20. Integrability, exact solutions and nonlinear dynamics of a nonisospectral integral-differential system
  21. Bounds for partition dimension of M-wheels
  22. Visual Analysis of Cylindrically Polarized Light Beams’ Focal Characteristics by Path Integral
  23. Analysis of repulsive central universal force field on solar and galactic dynamics
  24. Solitary Wave Solution of Nonlinear PDEs Arising in Mathematical Physics
  25. Understanding quantum mechanics: a review and synthesis in precise language
  26. Plane Wave Reflection in a Compressible Half Space with Initial Stress
  27. Evaluation of the realism of a full-color reflection H2 analog hologram recorded on ultra-fine-grain silver-halide material
  28. Graph cutting and its application to biological data
  29. Time fractional modified KdV-type equations: Lie symmetries, exact solutions and conservation laws
  30. Exact solutions of equal-width equation and its conservation laws
  31. MHD and Slip Effect on Two-immiscible Third Grade Fluid on Thin Film Flow over a Vertical Moving Belt
  32. Vibration Analysis of a Three-Layered FGM Cylindrical Shell Including the Effect Of Ring Support
  33. Hybrid censoring samples in assessment the lifetime performance index of Chen distributed products
  34. Study on the law of coal resistivity variation in the process of gas adsorption/desorption
  35. Mapping of Lineament Structures from Aeromagnetic and Landsat Data Over Ankpa Area of Lower Benue Trough, Nigeria
  36. Beta Generalized Exponentiated Frechet Distribution with Applications
  37. INS/gravity gradient aided navigation based on gravitation field particle filter
  38. Electrodynamics in Euclidean Space Time Geometries
  39. Dynamics and Wear Analysis of Hydraulic Turbines in Solid-liquid Two-phase Flow
  40. On Numerical Solution Of The Time Fractional Advection-Diffusion Equation Involving Atangana-Baleanu-Caputo Derivative
  41. New Complex Solutions to the Nonlinear Electrical Transmission Line Model
  42. The effects of quantum spectrum of 4 + n-dimensional water around a DNA on pure water in four dimensional universe
  43. Quantum Phase Estimation Algorithm for Finding Polynomial Roots
  44. Vibration Equation of Fractional Order Describing Viscoelasticity and Viscous Inertia
  45. The Errors Recognition and Compensation for the Numerical Control Machine Tools Based on Laser Testing Technology
  46. Evaluation and Decision Making of Organization Quality Specific Immunity Based on MGDM-IPLAO Method
  47. Key Frame Extraction of Multi-Resolution Remote Sensing Images Under Quality Constraint
  48. Influences of Contact Force towards Dressing Contiguous Sense of Linen Clothing
  49. Modeling and optimization of urban rail transit scheduling with adaptive fruit fly optimization algorithm
  50. The pseudo-limit problem existing in electromagnetic radiation transmission and its mathematical physics principle analysis
  51. Chaos synchronization of fractional–order discrete–time systems with different dimensions using two scaling matrices
  52. Stress Characteristics and Overload Failure Analysis of Cemented Sand and Gravel Dam in Naheng Reservoir
  53. A Big Data Analysis Method Based on Modified Collaborative Filtering Recommendation Algorithms
  54. Semi-supervised Classification Based Mixed Sampling for Imbalanced Data
  55. The Influence of Trading Volume, Market Trend, and Monetary Policy on Characteristics of the Chinese Stock Exchange: An Econophysics Perspective
  56. Estimation of sand water content using GPR combined time-frequency analysis in the Ordos Basin, China
  57. Special Issue Applications of Nonlinear Dynamics
  58. Discrete approximate iterative method for fuzzy investment portfolio based on transaction cost threshold constraint
  59. Multi-objective performance optimization of ORC cycle based on improved ant colony algorithm
  60. Information retrieval algorithm of industrial cluster based on vector space
  61. Parametric model updating with frequency and MAC combined objective function of port crane structure based on operational modal analysis
  62. Evacuation simulation of different flow ratios in low-density state
  63. A pointer location algorithm for computer visionbased automatic reading recognition of pointer gauges
  64. A cloud computing separation model based on information flow
  65. Optimizing model and algorithm for railway freight loading problem
  66. Denoising data acquisition algorithm for array pixelated CdZnTe nuclear detector
  67. Radiation effects of nuclear physics rays on hepatoma cells
  68. Special issue: XXVth Symposium on Electromagnetic Phenomena in Nonlinear Circuits (EPNC2018)
  69. A study on numerical integration methods for rendering atmospheric scattering phenomenon
  70. Wave propagation time optimization for geodesic distances calculation using the Heat Method
  71. Analysis of electricity generation efficiency in photovoltaic building systems made of HIT-IBC cells for multi-family residential buildings
  72. A structural quality evaluation model for three-dimensional simulations
  73. WiFi Electromagnetic Field Modelling for Indoor Localization
  74. Modeling Human Pupil Dilation to Decouple the Pupillary Light Reflex
  75. Principal Component Analysis based on data characteristics for dimensionality reduction of ECG recordings in arrhythmia classification
  76. Blinking Extraction in Eye gaze System for Stereoscopy Movies
  77. Optimization of screen-space directional occlusion algorithms
  78. Heuristic based real-time hybrid rendering with the use of rasterization and ray tracing method
  79. Review of muscle modelling methods from the point of view of motion biomechanics with particular emphasis on the shoulder
  80. The use of segmented-shifted grain-oriented sheets in magnetic circuits of small AC motors
  81. High Temperature Permanent Magnet Synchronous Machine Analysis of Thermal Field
  82. Inverse approach for concentrated winding surface permanent magnet synchronous machines noiseless design
  83. An enameled wire with a semi-conductive layer: A solution for a better distibution of the voltage stresses in motor windings
  84. High temperature machines: topologies and preliminary design
  85. Aging monitoring of electrical machines using winding high frequency equivalent circuits
  86. Design of inorganic coils for high temperature electrical machines
  87. A New Concept for Deeper Integration of Converters and Drives in Electrical Machines: Simulation and Experimental Investigations
  88. Special Issue on Energetic Materials and Processes
  89. Investigations into the mechanisms of electrohydrodynamic instability in free surface electrospinning
  90. Effect of Pressure Distribution on the Energy Dissipation of Lap Joints under Equal Pre-tension Force
  91. Research on microstructure and forming mechanism of TiC/1Cr12Ni3Mo2V composite based on laser solid forming
  92. Crystallization of Nano-TiO2 Films based on Glass Fiber Fabric Substrate and Its Impact on Catalytic Performance
  93. Effect of Adding Rare Earth Elements Er and Gd on the Corrosion Residual Strength of Magnesium Alloy
  94. Closed-die Forging Technology and Numerical Simulation of Aluminum Alloy Connecting Rod
  95. Numerical Simulation and Experimental Research on Material Parameters Solution and Shape Control of Sandwich Panels with Aluminum Honeycomb
  96. Research and Analysis of the Effect of Heat Treatment on Damping Properties of Ductile Iron
  97. Effect of austenitising heat treatment on microstructure and properties of a nitrogen bearing martensitic stainless steel
  98. Special Issue on Fundamental Physics of Thermal Transports and Energy Conversions
  99. Numerical simulation of welding distortions in large structures with a simplified engineering approach
  100. Investigation on the effect of electrode tip on formation of metal droplets and temperature profile in a vibrating electrode electroslag remelting process
  101. Effect of North Wall Materials on the Thermal Environment in Chinese Solar Greenhouse (Part A: Experimental Researches)
  102. Three-dimensional optimal design of a cooled turbine considering the coolant-requirement change
  103. Theoretical analysis of particle size re-distribution due to Ostwald ripening in the fuel cell catalyst layer
  104. Effect of phase change materials on heat dissipation of a multiple heat source system
  105. Wetting properties and performance of modified composite collectors in a membrane-based wet electrostatic precipitator
  106. Implementation of the Semi Empirical Kinetic Soot Model Within Chemistry Tabulation Framework for Efficient Emissions Predictions in Diesel Engines
  107. Comparison and analyses of two thermal performance evaluation models for a public building
  108. A Novel Evaluation Method For Particle Deposition Measurement
  109. Effect of the two-phase hybrid mode of effervescent atomizer on the atomization characteristics
  110. Erratum
  111. Integrability analysis of the partial differential equation describing the classical bond-pricing model of mathematical finance
  112. Erratum to: Energy converting layers for thin-film flexible photovoltaic structures
https://doi.org/10.1515/phys-2019-0092
Schlagwörter für diesen Artikel
quality constraint; multi resolution; remote sensing image; key frame; extraction; clustering operation
Creative Commons
BY 4.0

Artikel in diesem Heft

  1. Regular Articles
  2. Non-equilibrium Phase Transitions in 2D Small-World Networks: Competing Dynamics
  3. Harmonic waves solution in dual-phase-lag magneto-thermoelasticity
  4. Multiplicative topological indices of honeycomb derived networks
  5. Zagreb Polynomials and redefined Zagreb indices of nanostar dendrimers
  6. Solar concentrators manufacture and automation
  7. Idea of multi cohesive areas - foundation, current status and perspective
  8. Derivation method of numerous dynamics in the Special Theory of Relativity
  9. An application of Nwogu’s Boussinesq model to analyze the head-on collision process between hydroelastic solitary waves
  10. Competing Risks Model with Partially Step-Stress Accelerate Life Tests in Analyses Lifetime Chen Data under Type-II Censoring Scheme
  11. Group velocity mismatch at ultrashort electromagnetic pulse propagation in nonlinear metamaterials
  12. Investigating the impact of dissolved natural gas on the flow characteristics of multicomponent fluid in pipelines
  13. Analysis of impact load on tubing and shock absorption during perforating
  14. Energy characteristics of a nonlinear layer at resonant frequencies of wave scattering and generation
  15. Ion charge separation with new generation of nuclear emulsion films
  16. On the influence of water on fragmentation of the amino acid L-threonine
  17. Formulation of heat conduction and thermal conductivity of metals
  18. Displacement Reliability Analysis of Submerged Multi-body Structure’s Floating Body for Connection Gaps
  19. Deposits of iron oxides in the human globus pallidus
  20. Integrability, exact solutions and nonlinear dynamics of a nonisospectral integral-differential system
  21. Bounds for partition dimension of M-wheels
  22. Visual Analysis of Cylindrically Polarized Light Beams’ Focal Characteristics by Path Integral
  23. Analysis of repulsive central universal force field on solar and galactic dynamics
  24. Solitary Wave Solution of Nonlinear PDEs Arising in Mathematical Physics
  25. Understanding quantum mechanics: a review and synthesis in precise language
  26. Plane Wave Reflection in a Compressible Half Space with Initial Stress
  27. Evaluation of the realism of a full-color reflection H2 analog hologram recorded on ultra-fine-grain silver-halide material
  28. Graph cutting and its application to biological data
  29. Time fractional modified KdV-type equations: Lie symmetries, exact solutions and conservation laws
  30. Exact solutions of equal-width equation and its conservation laws
  31. MHD and Slip Effect on Two-immiscible Third Grade Fluid on Thin Film Flow over a Vertical Moving Belt
  32. Vibration Analysis of a Three-Layered FGM Cylindrical Shell Including the Effect Of Ring Support
  33. Hybrid censoring samples in assessment the lifetime performance index of Chen distributed products
  34. Study on the law of coal resistivity variation in the process of gas adsorption/desorption
  35. Mapping of Lineament Structures from Aeromagnetic and Landsat Data Over Ankpa Area of Lower Benue Trough, Nigeria
  36. Beta Generalized Exponentiated Frechet Distribution with Applications
  37. INS/gravity gradient aided navigation based on gravitation field particle filter
  38. Electrodynamics in Euclidean Space Time Geometries
  39. Dynamics and Wear Analysis of Hydraulic Turbines in Solid-liquid Two-phase Flow
  40. On Numerical Solution Of The Time Fractional Advection-Diffusion Equation Involving Atangana-Baleanu-Caputo Derivative
  41. New Complex Solutions to the Nonlinear Electrical Transmission Line Model
  42. The effects of quantum spectrum of 4 + n-dimensional water around a DNA on pure water in four dimensional universe
  43. Quantum Phase Estimation Algorithm for Finding Polynomial Roots
  44. Vibration Equation of Fractional Order Describing Viscoelasticity and Viscous Inertia
  45. The Errors Recognition and Compensation for the Numerical Control Machine Tools Based on Laser Testing Technology
  46. Evaluation and Decision Making of Organization Quality Specific Immunity Based on MGDM-IPLAO Method
  47. Key Frame Extraction of Multi-Resolution Remote Sensing Images Under Quality Constraint
  48. Influences of Contact Force towards Dressing Contiguous Sense of Linen Clothing
  49. Modeling and optimization of urban rail transit scheduling with adaptive fruit fly optimization algorithm
  50. The pseudo-limit problem existing in electromagnetic radiation transmission and its mathematical physics principle analysis
  51. Chaos synchronization of fractional–order discrete–time systems with different dimensions using two scaling matrices
  52. Stress Characteristics and Overload Failure Analysis of Cemented Sand and Gravel Dam in Naheng Reservoir
  53. A Big Data Analysis Method Based on Modified Collaborative Filtering Recommendation Algorithms
  54. Semi-supervised Classification Based Mixed Sampling for Imbalanced Data
  55. The Influence of Trading Volume, Market Trend, and Monetary Policy on Characteristics of the Chinese Stock Exchange: An Econophysics Perspective
  56. Estimation of sand water content using GPR combined time-frequency analysis in the Ordos Basin, China
  57. Special Issue Applications of Nonlinear Dynamics
  58. Discrete approximate iterative method for fuzzy investment portfolio based on transaction cost threshold constraint
  59. Multi-objective performance optimization of ORC cycle based on improved ant colony algorithm
  60. Information retrieval algorithm of industrial cluster based on vector space
  61. Parametric model updating with frequency and MAC combined objective function of port crane structure based on operational modal analysis
  62. Evacuation simulation of different flow ratios in low-density state
  63. A pointer location algorithm for computer visionbased automatic reading recognition of pointer gauges
  64. A cloud computing separation model based on information flow
  65. Optimizing model and algorithm for railway freight loading problem
  66. Denoising data acquisition algorithm for array pixelated CdZnTe nuclear detector
  67. Radiation effects of nuclear physics rays on hepatoma cells
  68. Special issue: XXVth Symposium on Electromagnetic Phenomena in Nonlinear Circuits (EPNC2018)
  69. A study on numerical integration methods for rendering atmospheric scattering phenomenon
  70. Wave propagation time optimization for geodesic distances calculation using the Heat Method
  71. Analysis of electricity generation efficiency in photovoltaic building systems made of HIT-IBC cells for multi-family residential buildings
  72. A structural quality evaluation model for three-dimensional simulations
  73. WiFi Electromagnetic Field Modelling for Indoor Localization
  74. Modeling Human Pupil Dilation to Decouple the Pupillary Light Reflex
  75. Principal Component Analysis based on data characteristics for dimensionality reduction of ECG recordings in arrhythmia classification
  76. Blinking Extraction in Eye gaze System for Stereoscopy Movies
  77. Optimization of screen-space directional occlusion algorithms
  78. Heuristic based real-time hybrid rendering with the use of rasterization and ray tracing method
  79. Review of muscle modelling methods from the point of view of motion biomechanics with particular emphasis on the shoulder
  80. The use of segmented-shifted grain-oriented sheets in magnetic circuits of small AC motors
  81. High Temperature Permanent Magnet Synchronous Machine Analysis of Thermal Field
  82. Inverse approach for concentrated winding surface permanent magnet synchronous machines noiseless design
  83. An enameled wire with a semi-conductive layer: A solution for a better distibution of the voltage stresses in motor windings
  84. High temperature machines: topologies and preliminary design
  85. Aging monitoring of electrical machines using winding high frequency equivalent circuits
  86. Design of inorganic coils for high temperature electrical machines
  87. A New Concept for Deeper Integration of Converters and Drives in Electrical Machines: Simulation and Experimental Investigations
  88. Special Issue on Energetic Materials and Processes
  89. Investigations into the mechanisms of electrohydrodynamic instability in free surface electrospinning
  90. Effect of Pressure Distribution on the Energy Dissipation of Lap Joints under Equal Pre-tension Force
  91. Research on microstructure and forming mechanism of TiC/1Cr12Ni3Mo2V composite based on laser solid forming
  92. Crystallization of Nano-TiO2 Films based on Glass Fiber Fabric Substrate and Its Impact on Catalytic Performance
  93. Effect of Adding Rare Earth Elements Er and Gd on the Corrosion Residual Strength of Magnesium Alloy
  94. Closed-die Forging Technology and Numerical Simulation of Aluminum Alloy Connecting Rod
  95. Numerical Simulation and Experimental Research on Material Parameters Solution and Shape Control of Sandwich Panels with Aluminum Honeycomb
  96. Research and Analysis of the Effect of Heat Treatment on Damping Properties of Ductile Iron
  97. Effect of austenitising heat treatment on microstructure and properties of a nitrogen bearing martensitic stainless steel
  98. Special Issue on Fundamental Physics of Thermal Transports and Energy Conversions
  99. Numerical simulation of welding distortions in large structures with a simplified engineering approach
  100. Investigation on the effect of electrode tip on formation of metal droplets and temperature profile in a vibrating electrode electroslag remelting process
  101. Effect of North Wall Materials on the Thermal Environment in Chinese Solar Greenhouse (Part A: Experimental Researches)
  102. Three-dimensional optimal design of a cooled turbine considering the coolant-requirement change
  103. Theoretical analysis of particle size re-distribution due to Ostwald ripening in the fuel cell catalyst layer
  104. Effect of phase change materials on heat dissipation of a multiple heat source system
  105. Wetting properties and performance of modified composite collectors in a membrane-based wet electrostatic precipitator
  106. Implementation of the Semi Empirical Kinetic Soot Model Within Chemistry Tabulation Framework for Efficient Emissions Predictions in Diesel Engines
  107. Comparison and analyses of two thermal performance evaluation models for a public building
  108. A Novel Evaluation Method For Particle Deposition Measurement
  109. Effect of the two-phase hybrid mode of effervescent atomizer on the atomization characteristics
  110. Erratum
  111. Integrability analysis of the partial differential equation describing the classical bond-pricing model of mathematical finance
  112. Erratum to: Energy converting layers for thin-film flexible photovoltaic structures
Jetzt anmelden und 20% sparen
Institutioneller Zugang
Wie funktioniert Authentifizierung?
Haben Sie eine Idee, wie wir unsere Website verbessern können?
Bitte schreiben Sie uns.
© 2025 De Gruyter Brill
Heruntergeladen am 8.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/phys-2019-0092/html
Button zum nach oben scrollen