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Enhanced Modified Decision Based Unsymmetric Trimmed Median Filter for Salt and Pepper Noise Removal

E. Jebamalar Leavline, D. Asir Antony Gnana Singh


Digital images are often corrupted by impulse noise during acquisition and transmission. This requires the images to be processed to remove noise before it can be used in any application. Image denoising involves the manipulation of image data to produce a high quality image. In this work, we propose an Enhanced Modified Decision Based Unsymmetric Trimmed Median Filter for removal of high-density salt-and-pepper noise. Through experimental study, this filtering approach was proved effective to perform denoising of images with a noise density over 90%. Extensive simulations and direct comparisons were done with existing state-of-the-art techniques. The results are presented in terms of mean square error, peak signal-to-noise ratio, and image enhancement factor.


salt-and-pepper noise, spatial filtering, trimmed median filter, high density noise removal, decision based algorithm.

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