13 Color constancy adjustment techniques
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Abstract
This chapter presents an overview on color constancy adjustment techniques. The concept of color constancy within digital images is first introduced and then some of the recent color correction methods are discussed. Some publicly available benchmark standard image datasets, which are used by the researchers to assess the performance of the color correction methods are introduced. These datasets contain both real and syntactical images of scenes illuminated by a single or multiple light source/s. Color constancy quality assessment measures, which are widely used in the literature, are also detailed. Finally, the performance of different color correction methods on images of different benchmark image datasets is assessed and compared. The chapter demonstrates that the learning-based approaches outperform the statistical based algorithms at significantly higher computation costs. Moreover, their performances are very data-dependent, while recent statistical-based methods have slightly lower performance to those of the learning-based algorithms at significantly lower computation cost and data dependency.
Abstract
This chapter presents an overview on color constancy adjustment techniques. The concept of color constancy within digital images is first introduced and then some of the recent color correction methods are discussed. Some publicly available benchmark standard image datasets, which are used by the researchers to assess the performance of the color correction methods are introduced. These datasets contain both real and syntactical images of scenes illuminated by a single or multiple light source/s. Color constancy quality assessment measures, which are widely used in the literature, are also detailed. Finally, the performance of different color correction methods on images of different benchmark image datasets is assessed and compared. The chapter demonstrates that the learning-based approaches outperform the statistical based algorithms at significantly higher computation costs. Moreover, their performances are very data-dependent, while recent statistical-based methods have slightly lower performance to those of the learning-based algorithms at significantly lower computation cost and data dependency.
Kapitel in diesem Buch
- Frontmatter I
- Preface V
- Contents VII
- About the Editors IX
- List of Contributors XI
- 1 OpenCV libraries for computer vision 1
- 2 Data science, computer vision and machine learning for agriculture and natural resource management: an overview 23
- 3 Image caption generating system using convolutional neural networks and long short-term memory networks 55
- 4 Computer vision for healthcare applications 73
- 5 Mental disorder prediction using facial expression based on machine learning techniques 97
- 6 Neonatal monitoring system using IoT and object detection 109
- 7 Video surveillance fire detection and quick alarm systems 121
- 8 Face mask detection and crowd size estimation using IoT platform 135
- 9 Generative adversary networks novel trends in image processing 147
- 10 Computer vision-based approach for alphabetic recognition and Indian Sign Language recognition system 173
- 11 Automated healthcare system using gamification and AI-based chatbot 199
- 12 Prediction of MRI tumor condition through image segmentation using deep neural network approach 215
- 13 Color constancy adjustment techniques 243
- 14 Hyperspectral imaging and its applications for vein detection: a review 277
- 15 Detection of Augmented Facial Landmarks-based Face Swapping 307
- 16 Factors affecting the accuracy of a laser scanner 327
- Index 355
Kapitel in diesem Buch
- Frontmatter I
- Preface V
- Contents VII
- About the Editors IX
- List of Contributors XI
- 1 OpenCV libraries for computer vision 1
- 2 Data science, computer vision and machine learning for agriculture and natural resource management: an overview 23
- 3 Image caption generating system using convolutional neural networks and long short-term memory networks 55
- 4 Computer vision for healthcare applications 73
- 5 Mental disorder prediction using facial expression based on machine learning techniques 97
- 6 Neonatal monitoring system using IoT and object detection 109
- 7 Video surveillance fire detection and quick alarm systems 121
- 8 Face mask detection and crowd size estimation using IoT platform 135
- 9 Generative adversary networks novel trends in image processing 147
- 10 Computer vision-based approach for alphabetic recognition and Indian Sign Language recognition system 173
- 11 Automated healthcare system using gamification and AI-based chatbot 199
- 12 Prediction of MRI tumor condition through image segmentation using deep neural network approach 215
- 13 Color constancy adjustment techniques 243
- 14 Hyperspectral imaging and its applications for vein detection: a review 277
- 15 Detection of Augmented Facial Landmarks-based Face Swapping 307
- 16 Factors affecting the accuracy of a laser scanner 327
- Index 355
