Impulse noise is one of the major problems in digital image processing. Impulse noise can corrupt the images and also damage the fine details in the image. Different filtering algorithms are applied on images to remove the impulse noise that are present in image during acquisition. Corrupted pixels in image take either the minimum or maximum gray level. Image denoising filters are based on the median filter. Survey on Variants of median filters like weighted median filter, adaptive switching median filter, triststate switching median filter, modified decision based unsymmentrictristate median filter are discussed in his paper. KEYWORDS: Denoising, Filtering, weighted median filter, center weighted median filter, adaptive switching median filter.

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Quality of image is very important and needed thing while considering the importance of image in communication, satellite, defence purpose, analysis etc. Quality of image is generally affected during compression, down sampling, transmission, and by the effect of noise. Super-resolution of image comes in this concept. For the purpose of analyzing compressed biomedical image, proposed method is a solution. Low resolution biomedical image is taken as sam pIe input. To improve the resolution and quality of such image, artifact rem oval, adaptive regularization and pair-matching super resolution is used. For clarity enhancement, edge detection and error correcting methods are used. Both are interpolated to get resultant image. The final image will be a super-resolution (SR)image, free from noise. The proposed method had been compared with several existing methods and analyzed the performance using MSE and PSNR metrics.

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