Image De-noising Using Linear and Decision Based Median Filters
Keywords:
Filters, De-noising, density, PSNR, MSEAbstract
Image de-noising is the big problem in image based applications, whereas transferring images through all types of electronic communication. During the electronic communication the impulse noise is caused via uneven voltage. Such kind of noise is necessary to eliminate, using some filtering techniques. In this work, the linear and decision based median filtering (DBMF) techniques are used to eliminate the image impulse noise. In this approach can mainly preserve the image information, whereas suppressing impulsive noise. The proposed filtering techniques are studied with many simulation results using MATLAB. Utmost of earlier known methods are suitable for the de-noising of image corrupted with fewer noise density. Here a proposed decision based method has been offered which produce better performances than linear conventional filters. Finally to compare the quantitative analysis is made by Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) of different images.
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