Entropy in Image Analysis

doi:10.3390/books978-3-03921-093-0

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Entropy in Image Analysis

Edited by

June 2019

456 pages

ISBN978-3-03921-092-3 (Paperback)
ISBN978-3-03921-093-0 (PDF)

https://doi.org/10.3390/books978-3-03921-093-0

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This book is a reprint of the Special Issue Entropy in Image Analysis that was published in

Chemistry & Materials Science

Computer Science & Mathematics

Physical Sciences

Summary

Image analysis is a fundamental task for extracting information from images acquired across a range of different devices. Since reliable quantitative results are requested, image analysis requires highly sophisticated numerical and analytical methods—particularly for applications in medicine, security, and remote sensing, where the results of the processing may consist of vitally important data. The contributions to this book provide a good overview of the most important demands and solutions concerning this research area. In particular, the reader will find image analysis applied for feature extraction, encryption and decryption of data, color segmentation, and in the support new technologies. In all the contributions, entropy plays a pivotal role.

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Keywords

image retrieval; multi-feature fusion; entropy; relevance feedback; chaotic system; image encryption; permutation-diffusion; SHA-256 hash value; dynamic index; entropy; keyframes; Shannon’s entropy; sign languages; video summarization; video skimming; image encryption; multiple-image encryption; two-dimensional chaotic economic map; security analysis; image encryption; chaotic cryptography; cryptanalysis; chosen-plaintext attack; image information entropy; blind image quality assessment (BIQA); information entropy, natural scene statistics (NSS); Weibull statistics; discrete cosine transform (DCT); ultrasound; hepatic steatosis; Shannon entropy; fatty liver; metabolic syndrome; multi-exposure image fusion; texture information entropy; adaptive selection; patch structure decomposition; image encryption; time-delay; random insertion; information entropy; chaotic map; uncertainty assessment; deep neural network; random forest; Shannon entropy; positron emission tomography; reconstruction; field of experts; additive manufacturing; 3D prints; 3D scanning; image entropy; depth maps; surface quality assessment; machine vision; image analysis; Arimoto entropy; free-form deformations; normalized divergence measure; gradient distributions; nonextensive entropy; non-rigid registration; pavement; macrotexture; 3-D digital imaging; entropy; decay trend; discrete entropy; infrared images; low contrast; multiscale top-hat transform; image encryption; DNA encoding; chaotic cryptography; cryptanalysis; image privacy; computer aided diagnostics; colonoscopy; Rényi entropies; structural entropy; spatial filling factor; binary image; Cantor set; Hénon map; Minkowski island; prime-indexed primes; Ramanujan primes; Kapur’s entropy; color image segmentation; whale optimization algorithm; differential evolution; hybrid algorithm; Otsu method; image encryption; dynamic filtering; DNA computing; 3D Latin cube; permutation; diffusion; fuzzy entropy; electromagnetic field optimization; chaotic strategy; color image segmentation; multilevel thresholding; contrast enhancement; sigmoid; Tsallis statistics; q-exponential; q-sigmoid; q-Gaussian; ultra-sound images; person re-identification; image analysis; hash layer; quantization loss; Hamming distance; cross-entropy loss; image entropy; Shannon entropy; generalized entropies; image processing; image segmentation; medical imaging; remote sensing; security