A New Iterative Fir Filter for Image and Video Restoration
(0) Image and video filtering is a key image-processing task in computer vision especially in noisy environment. In most of the cases the noise source is unknown and hence posses a major difficulty in the filtering operation. In this paper we present an error-correction based learning approach for iterative filtering. A new FIR filter is designed in which the filter coefficients are updated based on Widrow-Hoffrule. Unlike the standard filter the proposed filter has me ability to remove noise without the a priori knowledge of the noise. Experimental result shows that the proposed filter efficiently removes the noise and preserves the edges in the image. We demonstrate the capability of the proposed algorithm by testing it on standard images infected by Gaussian noise and on a real time video containing inherent noise. Experimental result shows that the proposed filter is better than some of the existing standard filters..
Neural Network Error-correction Learning Image Restoration Gaussian Noise Image Processing.
Nitin Rakesh Prasad ParthaP. Mondal Rajan Kanhirodan
Department of Instrumentation,Indian Institute of Science, Bangalore 560012, India. Department of Physics,Indian Institute of Science, Bangalore 560012, India.
国际会议
Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)
北京
英文
777-782
2006-07-17（万方平台首次上网日期，不代表论文的发表时间）