Reprint
Entropy in Image Analysis II
Edited by
October 2020
394 pages
- ISBN978-3-03943-160-1 (Hardback)
- ISBN978-3-03943-161-8 (PDF)
This book is a reprint of the Special Issue Entropy in Image Analysis II that was published in
Chemistry & Materials Science
Computer Science & Mathematics
Physical Sciences
Summary
Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas.
Format
- Hardback
License
© 2020 by the authors; CC BY-NC-ND license
Keywords
image binarization; optical character recognition; local entropy filter; thresholding; image preprocessing; image entropy; image encryption; medical color images; RGB; chaotic system; crowd behavior analysis; salient crowd motion detection; repulsive force; direction entropy; node strength; Pompe disease; children; quantitative muscle ultrasound; texture-feature parametric imaging; image encryption; compound chaotic system; S-box; image information entropy; image chaotic encryption; cryptography; Latin cube; bit cube; chosen plaintext attack; atmosphere background; engine flame; infrared radiation; detectability; image quality evaluation; image retrieval; pooling method; convolutional neural network; feature distribution entropy; lossless compression; pattern classification; machine learning; malaria infection; entropy; Golomb–Rice codes; image entropy; image processing; image segmentation; weld segmentation; local entropy filter; weld evaluation; convolution neural network; image entropy; Python; Keras; RSNNS; MXNet; brain-computer interface (BCI); electroencephalography (EEG); motor imagery (MI); continuous wavelet transform (CWT); convolutional neural network (CNN); image encryption; hyperchaotic system; filtering; DNA computing; diffusion; deep neural network; entropy; data expansion; blind image quality assessment; saliency and distortion; human visual system; declining quality; data hiding; AMBTC; steganography; stego image; dictionary-based coding; pixel value adjusting; neuroaesthetics; symmetry; balance; complexity; chiaroscuro; normalized entropy; renaissance; portrait paintings; art history; art statistics; chaotic systems; image encryption; DNA coding; security analysis; blind image quality assessment; magnetic resonance images; entropy; non-maximum suppression; object detection; key-point detection; IoU; feature fusion; quasi-resonant Rossby/drift wave triads; Mordell elliptic curve; pseudo-random numbers; substitution box; steganography; nuclear spin generator; medical image; peak signal-to-noise ratio; key space calculation; Duchenne muscular dystrophy; entropy; ultrasound; backscattered signals; image entropy; image processing; image encryption; medical imaging; neural engineering; computer vision; crowd motion detection; security