Partition-based vector filtering technique for suppression of noise in digital color images

• Published in: IEEE transactions on image processing 2006-08, Vol.15 (8), p.2324-2342
• Main Authors: Ma, Zhonghua, Wu, Hong Ren, Feng, Dagan
• Format: Article
• Language: English
• Subjects: Adaptive estimation; Adaptive filters; Algorithms; Applied sciences; Center-weighted vector median (CWVM) filter; Color; Colored noise; Colorimetry - methods; Computer Graphics; constrained least mean-square (LMS) algorithm; Detection, estimation, filtering, equalization, prediction; digital color image restoration; Digital filters; Exact sciences and technology; Filtering; Filtration; Gain measurement; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image processing; Image restoration; Information Storage and Retrieval - methods; Information, signal and communications theory; Mathematical analysis; Measurement standards; Miscellaneous; Noise; Numerical Analysis, Computer-Assisted; partition-based adaptive vector (PBTVM) filter; Partitions; Performance gain; Reproducibility of Results; Restoration; Sensitivity and Specificity; Signal and communications theory; Signal processing; Signal Processing, Computer-Assisted; Signal, noise; Sports training; Studies; Telecommunications and information theory; Weightlifting
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2006.877066

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.