Entropy in Image Analysis
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, securi...
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Format: | Electronic Book Chapter |
Language: | English |
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MDPI - Multidisciplinary Digital Publishing Institute
2019
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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020 | |a books978-3-03921-093-0 | ||
020 | |a 9783039210923 | ||
020 | |a 9783039210930 | ||
040 | |a oapen |c oapen | ||
024 | 7 | |a 10.3390/books978-3-03921-093-0 |c doi | |
041 | 0 | |a eng | |
042 | |a dc | ||
072 | 7 | |a TBX |2 bicssc | |
100 | 1 | |a Sparavigna, Amelia Carolina |4 auth | |
245 | 1 | 0 | |a Entropy in Image Analysis |
260 | |b MDPI - Multidisciplinary Digital Publishing Institute |c 2019 | ||
300 | |a 1 electronic resource (456 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a 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. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by-nc-nd/4.0/ |2 cc |4 https://creativecommons.org/licenses/by-nc-nd/4.0/ | ||
546 | |a English | ||
650 | 7 | |a History of engineering & technology |2 bicssc | |
653 | |a keyframes | ||
653 | |a time-delay | ||
653 | |a whale optimization algorithm | ||
653 | |a multilevel thresholding | ||
653 | |a multi-exposure image fusion | ||
653 | |a additive manufacturing | ||
653 | |a patch structure decomposition | ||
653 | |a ultra-sound images | ||
653 | |a 3D scanning | ||
653 | |a Arimoto entropy | ||
653 | |a contrast enhancement | ||
653 | |a spatial filling factor | ||
653 | |a depth maps | ||
653 | |a image processing | ||
653 | |a 3D prints | ||
653 | |a differential evolution | ||
653 | |a field of experts | ||
653 | |a normalized divergence measure | ||
653 | |a image privacy | ||
653 | |a multiscale top-hat transform | ||
653 | |a q-exponential | ||
653 | |a texture information entropy | ||
653 | |a diffusion | ||
653 | |a hybrid algorithm | ||
653 | |a Weibull statistics | ||
653 | |a adaptive selection | ||
653 | |a nonextensive entropy | ||
653 | |a computer aided diagnostics | ||
653 | |a fatty liver | ||
653 | |a random forest | ||
653 | |a DNA encoding | ||
653 | |a low contrast | ||
653 | |a entropy | ||
653 | |a Minkowski island | ||
653 | |a fuzzy entropy | ||
653 | |a free-form deformations | ||
653 | |a person re-identification | ||
653 | |a chaotic system | ||
653 | |a DNA computing | ||
653 | |a pavement | ||
653 | |a information entropy | ||
653 | |a discrete entropy | ||
653 | |a Tsallis statistics | ||
653 | |a video skimming | ||
653 | |a prime-indexed primes | ||
653 | |a natural scene statistics (NSS) | ||
653 | |a Hénon map | ||
653 | |a q-sigmoid | ||
653 | |a image entropy | ||
653 | |a Shannon entropy | ||
653 | |a macrotexture | ||
653 | |a Shannon's entropy | ||
653 | |a binary image | ||
653 | |a multi-feature fusion | ||
653 | |a image analysis | ||
653 | |a uncertainty assessment | ||
653 | |a non-rigid registration | ||
653 | |a hash layer | ||
653 | |a Cantor set | ||
653 | |a dynamic filtering | ||
653 | |a deep neural network | ||
653 | |a security analysis | ||
653 | |a multiple-image encryption | ||
653 | |a Hamming distance | ||
653 | |a blind image quality assessment (BIQA) | ||
653 | |a q-Gaussian | ||
653 | |a remote sensing | ||
653 | |a decay trend | ||
653 | |a chaotic cryptography | ||
653 | |a chaotic strategy | ||
653 | |a cross-entropy loss | ||
653 | |a random insertion | ||
653 | |a metabolic syndrome | ||
653 | |a sign languages | ||
653 | |a generalized entropies | ||
653 | |a relevance feedback | ||
653 | |a image retrieval | ||
653 | |a two-dimensional chaotic economic map | ||
653 | |a cryptanalysis | ||
653 | |a infrared images | ||
653 | |a 3D Latin cube | ||
653 | |a SHA-256 hash value | ||
653 | |a gradient distributions | ||
653 | |a structural entropy | ||
653 | |a discrete cosine transform (DCT) | ||
653 | |a chaotic map | ||
653 | |a hepatic steatosis | ||
653 | |a machine vision | ||
653 | |a electromagnetic field optimization | ||
653 | |a security | ||
653 | |a image segmentation | ||
653 | |a quantization loss | ||
653 | |a colonoscopy | ||
653 | |a video summarization | ||
653 | |a permutation | ||
653 | |a Kapur's entropy | ||
653 | |a surface quality assessment | ||
653 | |a permutation-diffusion | ||
653 | |a Ramanujan primes | ||
653 | |a Rényi entropies | ||
653 | |a chosen-plaintext attack | ||
653 | |a image encryption | ||
653 | |a dynamic index | ||
653 | |a color image segmentation | ||
653 | |a ultrasound | ||
653 | |a Otsu method | ||
653 | |a sigmoid | ||
653 | |a reconstruction | ||
653 | |a image information entropy | ||
653 | |a 3-D digital imaging | ||
653 | |a positron emission tomography | ||
653 | |a medical imaging | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/1378 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/46558 |7 0 |z DOAB: description of the publication |