A multi-resolution transform for deblurring of images in the presence of impulse noise for real-time images Online publication date: Sat, 04-Mar-2017
by J. Amudha; R. Sudhakar
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 23, No. 2/3/4, 2017
Abstract: Noise in an image tends to reduce the quality of the image by modifying the contrast and resolution and thereby making the process of extraction of information from the image is a challenging task. Deblurring of images in the presence of noise as it may be impulsive or multiplicative is a challenging task. It is essentially an issue of the trade-off between deblurring and denoising. A non-subsampled Contourlet transform has been used in a hybrid approach to address the trade-off factor in this paper. Removal of blur using Point Spread Function (PSF) or other methods introduces an amplification of noise in high-frequency regions of the image. The proposed work exploits the directionality features of the Contourlet transform to provide a balance in the optimisation problem. The experimentations have been conducted on standard test images and performance measured in terms of Peak Signal to Noise Ratio and Mean Squared Error.
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