Enhancement of JPEG-Compressed Images by Re-application of JPEG
Journal of VLSI Signal Processing Systems - Special issue on multimedia signal processing
DCC '01 Proceedings of the Data Compression Conference
Combined image compression and denoising using wavelets
Image Communication
A survey of RST invariant image watermarking algorithms
ACM Computing Surveys (CSUR)
Denoising by sparse approximation: error bounds based on rate-distortion theory
EURASIP Journal on Applied Signal Processing
Lossy compression and curvelet thresholding for image denoising
International Journal of Information and Communication Technology
Simultaneous MAP-based video denoising and rate-distortion optimized video encoding
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Signal Processing
A context quantization approach to universal denoising
IEEE Transactions on Signal Processing
Robust edge extraction for Swissranger SR-3000 range images
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Rate distortion and denoising of individual data using Kolmogorov complexity
IEEE Transactions on Information Theory
Optimal image restoration using HVS-based rate-distortion curves
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
Kolmogorov complexity with error
STACS'06 Proceedings of the 23rd Annual conference on Theoretical Aspects of Computer Science
Original Articles: Time-scale energy based analysis of contours of real-world shapes
Mathematics and Computers in Simulation
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We present a novel technique for the design of filters for random noise, leading to a class of filters called Occam filters. The essence of the technique is that when a lossy data compression algorithm is applied to a noisy signal with the allowed loss set equal to the noise strength, the loss and the noise tend to cancel rather than add. We give two illustrative applications of the technique to univariate signals. We also prove asymptotic convergence bounds on the effectiveness of Occam filters