Название: Digital Image Enhancement and Reconstruction
Автор: Shyam Singh Rajput, Nafis Uddin Khan, Amit Kumar Singh
Издательство: Academic Press/Elsevier
Серия: Hybrid Computational Intelligence for Pattern Analysis and Understanding
Год: 2023
Страниц: 369
Язык: английский
Формат: pdf
Размер: 18.7 MB
Digital Image Enhancement and Reconstruction: Techniques and Applications explores different concepts and techniques used for the enhancement as well as reconstruction of low-quality images. Most real-life applications require good quality images to gain maximum performance, however, the quality of the images captured in real-world scenarios is often very unsatisfactory. Most commonly, images are noisy, blurry, hazy, tiny, and hence need to pass through image enhancement and/or reconstruction algorithms before they can be processed by image analysis applications. This book comprehensively explores application-specific enhancement and reconstruction techniques including satellite image enhancement, face hallucination, low-resolution face recognition, medical image enhancement and reconstruction, reconstruction of underwater images, text image enhancement, biometrics, etc. Deep Learning (DL) is one of the AI algorithms. The Convolutional Neural Network (CNN) has shown great potential in image recognition and has made many attempts in the field of IE of underlying vision. For example, the CNN can convert the IE problems into the regression from the degraded low-quality image to the original high-quality clear image, and the End-To-End (ETE) network training is realized through the sample pairs of low-quality image and high-quality image to learn and obtain this regression mapping.
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