Bio-Inspired Computation and Applications in Image Processing

Content: 
Front matter,Copyright,List of Contributors,About the editors,PrefaceEntitled to full textChapter 1 - Bio-inspired computation and its applications in image processing: an overview, Pages 1-24
Chapter 2 - Fine-tuning enhanced probabilistic neural networks using metaheuristic-driven optimization, Pages 25-45
Chapter 3 - Fine-tuning deep belief networks using cuckoo search, Pages 47-59
Chapter 4 - Improved weighted thresholded histogram equalization algorithm for digital image contrast enhancement using the bat algorithm, Pages 61-86
Chapter 5 - Ground-glass opacity nodules detection and segmentation using the snake model, Pages 87-104
Chapter 6 - Mobile object tracking using the modified cuckoo search, Pages 105-130
Chapter 7 - Toward optimal watermarking of grayscale images using the multiple scaling factor–based cuckoo search technique, Pages 131-155
Chapter 8 - Bat algorithm–based automatic clustering method and its application in image processing, Pages 157-185
Chapter 9 - Multitemporal remote sensing image classification by nature- inspired techniques, Pages 187-219
Chapter 10 - Firefly algorithm for optimized nonrigid demons registration, Pages 221-237
Chapter 11 - Minimizing the mode-change latency in real-time image processing applications, Pages 239-268
Chapter 12 - Learning OWA filters parameters for SAR imagery with multiple polarizations, Pages 269-284
Chapter 13 - Oil reservoir quality assisted by machine learning and evolutionary computation, Pages 285-310
Chapter 14 - Solving imbalanced dataset problems for high-dimensional image processing by swarm optimization, Pages 311-321
Chapter 15 - Retinal image vasculature analysis software (RIVAS), Pages 323-345
Index, Pages 347-353