Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1507
Title: An adaptive constrained least square approach for removing blocking effect
Authors: Hong, SW
Chan, YH 
Siu, WC 
Keywords: Computational complexity
Computer simulation
Constraint theory
Estimation
Functions
Image compression
Image reconstruction
Least squares approximations
Issue Date: 1995
Publisher: IEEE
Source: 1995 IEEE International Symposium on Circuits and Systems : Seattle, Washington, USA, April 30-May 3, 1995, p. 773-776 How to cite?
Abstract: This paper presents a new adaptive objective function based on the regularized iterative block reduction technique for low-bit rate transform coded images. Also, a better initial estimate for the regularization approach is presented. Two types of prior knowledge are used: the first type bounds the maximum tolerable error (roughness), and the second type restricts the high-frequency content (smoothness) of the restored images. Computer simulations showed that the new adaptive objective function with the proposed initial estimate performed better on both subjective and objective measures than did a previously proposed objective function.
URI: http://hdl.handle.net/10397/1507
ISBN: 0-7803-2127-8
Rights: © 1995 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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