Image processing and analysis - variational, PDE, wavelet, and stochastic methods
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چکیده
nonlinear functional analysis and its applications iii variational methods and optimization PDF remote sensing second edition models and methods for image processing PDF remote sensing third edition models and methods for image processing PDF guide to signals and patterns in image processing foundations methods and applications PDF introduction to image processing and analysis PDF principles of digital image processing advanced methods undergraduate topics in computer science PDF image processing analysis and machine vision PDF image acquisition and processing with labview image processing series PDF wavelet transform techniques for image resolution PDF sparse image and signal processing wavelets and related geometric multiscale analysis PDF nonstandard methods in stochastic analysis and mathematical physics dover books on mathematics PDF solution manual wavelet tour of signal processing PDF remote sensing image fusion signal and image processing of earth observations PDF image understanding using sparse representations synthesis lectures on image video and multimedia processing PDF
منابع مشابه
Review of "Image processing and analysis: variational, PDE, Wavelet, and Stochastic methods" by Tony F. Chan and Jianhong (Jackie) Shen
Image processing is an important component of modern technologies because human depends so much on the visual information than other creatures. Image is better than any other information form for us to perceive. Among our information about the world, 99% is perceived with our eyes [1]. Image processing has traditionally been an area in the engineering community. The basic tools are Fourier anal...
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There are many unavoidable noise interferences in image acquisition and transmission. To make it better for subsequent processing, the noise in the image should be removed in advance. There are many kinds of image noises, mainly including salt and pepper noise and Gaussian noise. This paper focuses on the research of the Gaussian noise removal. It introduces many wavelet threshold denoising alg...
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Wavelet transformation is one of the most practical mathematical transformations in the field of image processing, especially image and signal processing. Depending on the nature of the multiresolution analysis, Wavelet transformation become more accessible and powerful tools. In this paper, we refer to the mathematical foundations of this transformation. Introduction: The...
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Image restoration is an essential preprocessing step for many image analysis applications. In any image restoration techniques, keeping structure of the image unchanged is very important. Such structure in an image often corresponds to the region discontinuities and edges. The techniques based on partial differential equations, such as the heat equations, are receiving considerable attention i...
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Inspired by papers of Vese–Osher [OV02] and Osher–Solé–Vese [OSV02] we present a wavelet–based treatment of variational problems arising in the field of image processing. In particular, we follow their approach and discuss a special class of variational functionals that induce a decomposition of images into oscillating and cartoon components and possibly an appropriate ‘noise’ component. In the...
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