Entropy in Image Analysis III
Sparavigna, Amelia Carolina (editor)
Image analysis can be applied to rich and assorted scenarios; therefore, the aim of this recent research field is not only to mimic the human vision system. Image analysis is the main methods that computers are using today, and there is body of knowledge that they will be able to manage in a totally unsupervised manner in future, thanks to their artificial intelligence. The articles published in the book clearly show such a future.
KeywordsNewton-Raphson’s method; chaos; image encryption/decryption; security analysis; image encryption; cryptanalysis; hyper-chaotic; ribonucleic acid; color image encryption; transformed Zigzag; image segmentation; computer-assisted diagnosis; machine learning; spleen injury detection; hyperchaotic; permutation; diffusion; multiple bit operation; circular-step wedge; contrast-detail; mutual information; visible ratio; anode heel effect; prior information; entropy; fwi; regularization; inverse problems; bat optimization; human crowd behavior (HCB); improved entropy (IE); Jaccard similarity; multi-person counting; particles gradient motion (PGM); speeded up robust features (SURF); Retinex; image enhancement; gamma correction; low-light image; HSV color space; scan route; Hilbert curve; run-length-based entropy coding; image and video compression; secure communication; cellular neural network; power-divergence measure; computed tomography; iterative reconstruction; maximum-likelihood expectation-maximization method; continuous-time image reconstruction; n/a
Webshop linkhttps://mdpi.com/books/pdfview ...
Publication date and placeBasel, 2022
Technology: general issues
History of engineering & technology