Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1871
Title: Partition-based vector filtering technique for suppression of noise in digital color images
Authors: Ma, Z
Wu, HR
Feng, DD
Keywords: Center-weighted vector median (CWVM) filter
Constrained least mean-square (LMS) algorithm
Digital color image restoration
Partition-based adaptive vector (PBTVM) filter
Issue Date: Aug-2006
Publisher: IEEE
Source: IEEE transactions on image processing, Aug. 2006, v. 15, no. 8, p. 2324-2342 How to cite?
Journal: IEEE transactions on image processing 
Abstract: A partition-based adaptive vector filter is proposed for the restoration of corrupted digital color images. The novelty of the filter lies in its unique three-stage adaptive estimation. The local image structure is first estimated by a series of center-weighted reference filters. Then the distances between the observed central pixel and estimated references are utilized to classify the local inputs into one of preset structure partition cells. Finally, a weighted filtering operation, indexed by the partition cell, is applied to the estimated references in order to restore the central pixel value. The weighted filtering operation is optimized off-line for each partition cell to achieve the best tradeoff between noise suppression and structure preservation. Recursive filtering operation and recursive weight training are also investigated to further boost the restoration performance. The proposed filter has demonstrated satisfactory results in suppressing many distinct types of noise in natural color images. Noticeable performance gains are demonstrated over other prior-art methods in terms of standard objective measurements, the visual image quality and the computational complexity.
URI: http://hdl.handle.net/10397/1871
ISSN: 1057-7149
DOI: 10.1109/TIP.2006.877066
Rights: © 2006 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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