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» The Use of Residuals in Image Denoising
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WSCG
2004
166views more  WSCG 2004»
15 years 1 months ago
De-noising and Recovering Images Based on Kernel PCA Theory
Principal Component Analysis (PCA) is a basis transformation to diagonalize an estimate of the covariance matrix of input data and, the new coordinates in the Eigenvector basis ar...
Pengcheng Xi, Tao Xu
ICIP
2009
IEEE
14 years 9 months ago
Component-based image coding using non-local means filtering and an autoregressive texture model
While noise is usually regarded as a problem of the image formation process, we observe that it is also frequently part of natural texture. In this paper, we present a concept for...
Johannes Ballé, Bastian Jurczyk, Aleksandar...
117
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ICCV
2003
IEEE
16 years 1 months ago
Cumulative Residual Entropy, A New Measure of Information & its Application to Image Alignment
In this paper we use the cumulative distribution of a random variable to define the information content in it and use it to develop a novel measure of information that parallels S...
Fei Wang, Baba C. Vemuri, Murali Rao, Yunmei Chen
ICASSP
2010
IEEE
14 years 12 months ago
Fundamental limits of image denoising: Are we there yet?
In this paper, we study the fundamental performance limits of image denoising where the aim is to recover the original image from its noisy observation. Our study is based on a ge...
Priyam Chatterjee, Peyman Milanfar
CVPR
2009
IEEE
16 years 6 months ago
Image Registration by Minimization of Residual Complexity
Accurate denition of similarity measure is a key component in image registration. Most commonly used intensitybased similarity measures rely on the assumptions of independence ...
Andriy Myronenko, Xubo B. Song