Name
Abstract | ||
|---|---|---|
Images are often corrupted by impulse noise due to a noisy sensor or channel transmission errors. The goal of removing impulse noise is to suppress the noise while preserving the integrity of edge and detail information associated with the original image. In this paper, a generalized framework for median filtering based on a switching scheme, called multi-state median (MSM) filter, is proposed. By using a simple thresholding operation, the output of the proposed MSM filter is adaptively switched among those of a group of centre weighted median (CWM) filters having different centre weights. As a result, the MSM filter is equivalent to an adaptive CWM filter with a space varying center weight which is dependent on local signal characteristics. The effectiveness in noise suppression and detail preservation of the proposed filtering technique has been evaluated by extensive simulations, showing superior performance to other median based filters |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1109/ICASSP.2000.859270 | ICASSP |
Keywords | Field | DocType |
multi-state median filtering,noise suppression,median filters,impulse noise removal,different centre weight,msm filter,space varying center weight,impulse noise,thresholding operation,adaptive cwm filter,proposed msm filter,nonlinear techniques,centre weighted median,image denoising,image restoration,adaptive switching,centre weighted median filters,adaptive filters,detail information,filtering theory,interference suppression,local signal characteristics,image enhancement,detail preservation,multi-state median,median filter,detectors,pixel,sun,image processing,probability distribution,filtering,dynamic range | Computer vision,Median filter,Computer science,Salt-and-pepper noise,Filter (signal processing),Adaptive filter,Impulse noise,Artificial intelligence,Matched filter,Gaussian noise,Nonlinear filter | Conference |
Volume | ISSN | ISBN |
6 | 1520-6149 | 0-7803-6293-4 |
Citations | PageRank | References |
13 | 0.90 | 0 |
Authors | ||
2 | ||