10 Fusion of Multispectral and Panchromatic Images as an Optimization Problem
-
N. Banupriya
Abstract
The fusion system entails merging the high spatial resolution of PAN images with the high-spectral resolution of MS images to generate a hybrid image that carries each spatial and spectral information. However, this system is not truthful and requires cautious attention of diverse parameters including spatial and spectral residences as well as optimization strategies to gain good effects. This chapter gives an optimizationbased framework for image fusion, in which the fusion trouble is formulated as an optimization trouble with particular goals and constraints. The proposed framework pursuits to find the most suitable answer for image fusion by using both the spatial and spectral traits of the input images. By using an optimization method, the framework can efficiently manage the trade-off among spatial and spectral information, resulting in a composite image with improved spatial and spectral resolutions. The optimization hassle solved the usage of numerous strategies such as wavelet transform, linearblended mapping, and statistical techniques to attain the quality mixture of the input images.
Abstract
The fusion system entails merging the high spatial resolution of PAN images with the high-spectral resolution of MS images to generate a hybrid image that carries each spatial and spectral information. However, this system is not truthful and requires cautious attention of diverse parameters including spatial and spectral residences as well as optimization strategies to gain good effects. This chapter gives an optimizationbased framework for image fusion, in which the fusion trouble is formulated as an optimization trouble with particular goals and constraints. The proposed framework pursuits to find the most suitable answer for image fusion by using both the spatial and spectral traits of the input images. By using an optimization method, the framework can efficiently manage the trade-off among spatial and spectral information, resulting in a composite image with improved spatial and spectral resolutions. The optimization hassle solved the usage of numerous strategies such as wavelet transform, linearblended mapping, and statistical techniques to attain the quality mixture of the input images.
Chapters in this book
- Frontmatter I
- Contents V
- List of Authors IX
- 1 Medical Image Processing: A Multimodal Fusion Technique 1
- 2 Image Fusion Mathematics Theory and Practice 21
- 3 Current Trends in High-Resolution Image Reconstruction 43
- 4 Image Fusion Through Multiresolution Oversampled Decompositions 59
- 5 Mathematical Models for Remote Sensing Image Processing 75
- 6 Component Analysis and Medical Image Fusion 91
- 7 Soft Computing Approaches to Medical Image Fusion 105
- 8 Mathematical Techniques in Multispectral Image Fusion 119
- 9 Fusion of Artificial Intelligence and Machine Learning for Advanced Image Processing 135
- 10 Fusion of Multispectral and Panchromatic Images as an Optimization Problem 151
- 11 Image Fusion Using Optimization of Statistical Measurements 167
- 12 Empirical Mode Decomposition for Simultaneous Image Enhancement and Fusion 183
- 13 Multimodality Sensor Image Fusion 189
- 14 Medical Image Fusion Method by Deep Learning 207
- 15 Quaternion-Based Sparse Techniques for Multimodal and Multispectral Image Processing 223
- 16 Quaternion Neural Networks for Geometrical Operators in High-Dimensional Quaternion Space 239
- 17 Image Dehazing Using Quaternion Complex Algebra-Based Neural Networks 255
- 18 Deep Learning Model for Image Fusion and Accurate Classification of Remote Sensing Images 271
- 19 Multimodal Medical Supervised Image Fusion Method 297
- 20 Medical Image Fusion Using Deep Learning Mechanisms 315
- 21 Multifocus Image Fusion Using Content-Adaptive Blurring 339
- 22 Optimizing Top Precision Performance Measure of Content-Based Image Retrieval by Learning Similarity Function 349
- 23 Performance Evaluation of Image Fusion Techniques 361
- Index 373
Chapters in this book
- Frontmatter I
- Contents V
- List of Authors IX
- 1 Medical Image Processing: A Multimodal Fusion Technique 1
- 2 Image Fusion Mathematics Theory and Practice 21
- 3 Current Trends in High-Resolution Image Reconstruction 43
- 4 Image Fusion Through Multiresolution Oversampled Decompositions 59
- 5 Mathematical Models for Remote Sensing Image Processing 75
- 6 Component Analysis and Medical Image Fusion 91
- 7 Soft Computing Approaches to Medical Image Fusion 105
- 8 Mathematical Techniques in Multispectral Image Fusion 119
- 9 Fusion of Artificial Intelligence and Machine Learning for Advanced Image Processing 135
- 10 Fusion of Multispectral and Panchromatic Images as an Optimization Problem 151
- 11 Image Fusion Using Optimization of Statistical Measurements 167
- 12 Empirical Mode Decomposition for Simultaneous Image Enhancement and Fusion 183
- 13 Multimodality Sensor Image Fusion 189
- 14 Medical Image Fusion Method by Deep Learning 207
- 15 Quaternion-Based Sparse Techniques for Multimodal and Multispectral Image Processing 223
- 16 Quaternion Neural Networks for Geometrical Operators in High-Dimensional Quaternion Space 239
- 17 Image Dehazing Using Quaternion Complex Algebra-Based Neural Networks 255
- 18 Deep Learning Model for Image Fusion and Accurate Classification of Remote Sensing Images 271
- 19 Multimodal Medical Supervised Image Fusion Method 297
- 20 Medical Image Fusion Using Deep Learning Mechanisms 315
- 21 Multifocus Image Fusion Using Content-Adaptive Blurring 339
- 22 Optimizing Top Precision Performance Measure of Content-Based Image Retrieval by Learning Similarity Function 349
- 23 Performance Evaluation of Image Fusion Techniques 361
- Index 373
