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Adaptive Nonlinear Filter for Removal of Salt-Pepper Noise in Infrared Image  

Lee, Je-Il (국방과학연구소)
Kim, Sung-Hwan (서울시립대 전자전기컴퓨터공학부)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers D / v.55, no.9, 2006 , pp. 429-434 More about this Journal
Abstract
In this paper, detection based - adaptive windowed nonlinear filter(DB-AWNF) is proposed for removing salt-pepper noise in infrared image. This filter is composed of impulse detector and window-size-variable median filters. Impulse detector checks whether current pixel is impulse or not using range function and nonlinear location estimator. If impulse is detected, current pixel is filtered according to four kinds of local masks by use of median filter. If not, current pixel is delivered to output like identity filter. In Qualitative view, the proposed could have removed heavy corrupted noise up to 30% and reserved the details of image. In quantitative view, PSNR was measured. The proposed could have about 12-31[dB] more improved performance than those of median $(3{\times}3)$ filter and 13-29[dB] more improved performance than those of median $(5{\times}5)$ filter.
Keywords
Noise Removal; Impulse Detector; Nonlinear Location Estimator;
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