Robust Estimator Based On Median Filtering
Author(s):
Neha Sharma, Amrita
Keywords:
Impulse noise, Median filter, trimmed median filter, Pixel expansion, window size, PSNR, MSE, salt and pepper noise
Abstract
Noise free images are projected for good understanding of the data present in it. But due to many factors noise gets added and corrupts the image quality. Images are mainly affected by noise when they are transmitted over the unsecure channels. Mostly the images are contaminated by impulse noise due to defective communications. Various filters are applied to make the images noise free in order to achieve the images with no or minimum signal distortion. Median filters are best suited digital non linear filters to remove the impulse noise from the images while preserving the edges of the images. In contrast to the conventional median filters, a decision based median filter is applied to detect the noisy pixels so that filter is applied only to the corrupted pixels thereby preserving the image features and leaving the uncorrupted pixels unharmed. In this paper authors have presented a novel unsymmetrical trimmed median filter for removing the noise and to restore the gray scaled and coloured images highly infected by impulse noise. A decision based filter first figures out the noisy pixels and then changes them by median value if other than 0 and 255 values are present in the particular window and change the noisy pixels by the mean value of all the elements in the selected window if only 0’s and 255’s are present. The proposed algorithm is tested against different gray scaled and coloured images
Article Details
Unique Paper ID: 146555

Publication Volume & Issue: Volume 5, Issue 1

Page(s): 69 - 74
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