DocumentCode :
1214698
Title :
A robust structure-adaptive hybrid vector filter for color image restoration
Author :
Ma, Zhonghua ; Wu, Hong Ren ; Qiu, Bin
Author_Institution :
Sch. of Comput. Sci. & Software Eng., Monash Univ., Melbourne, Vic., Australia
Volume :
14
Issue :
12
fYear :
2005
Firstpage :
1990
Lastpage :
2001
Abstract :
A robust structure-adaptive hybrid vector filter is proposed for digital color image restoration in this paper. At each pixel location, the image vector (i.e., pixel) is first classified into several different signal activity categories by applying a modified quadtree decomposition to luminance component (image) of the input color image. A weight-adaptive vector filtering operation with an optimal window is then activated to achieve the best tradeoff between noise suppression and detail preservation. Through extensive simulation experiments conducted using a wide range of test color images, the filter has demonstrated superior performance to that of a number of well known benchmark techniques, in terms of both standard objective measurements and perceived image quality, in suppressing several distinct types of noise commonly considered in color image restoration, including Gaussian noise, impulse noise, and mixed noise.
Keywords :
Gaussian noise; adaptive filters; brightness; filtering theory; image colour analysis; image restoration; impulse noise; quadtrees; Gaussian noise; digital color image restoration; image quality; image vector; impulse noise; luminance component; mixed noise; noise suppression; quadtree decomposition; standard objective measurements; structure-adaptive hybrid vector filter; weight-adaptive vector filtering; Color; Colored noise; Digital filters; Filtering; Gaussian noise; Image restoration; Impulse testing; Pixel; Robustness; Signal restoration; Adaptive vector filtering; digital color image restoration; modified quadtree decomposition; structure-adaptive hybrid vector filter; Algorithms; Artificial Intelligence; Color; Colorimetry; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Pattern Recognition, Automated; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2005.857269
Filename :
1532300
Link To Document :
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