Abstract :
In this paper denoising techniques for AWGN corrupted image has been mainly focused. Visual information transfer in the form of digital images becomes a vast method of communication in the modern scenario, but the image obtained after transmission is many a times corrupted with noise. OWT SURE LET color denoising is based on linear expansion of thresholds LET and optimized using Steins unbiased risk estimate SURE . In this method, noisy color image is processed through Orthonormal Wavelet Transform OWT followed by thresholding of each channel wavelet coefficients. Finally, inverse wavelet transform is applied to bring back the result to the image domain. It efficiently exploits inter channel correlations. In order to remove the noise in multichannel images, OWT is applied on each channel. Shruti Badgainya | Prof. Pankaj Sahu | Prof. Vipul Awasthi "Image Denoising by OWT for Gaussian Noise Corrupted Images" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5 , August 2018, URL: https://www.ijtsrd.com/papers/ijtsrd18337.pdf Paper URL: http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/18337/image-denoising-by-owt-for-gaussian-noise-corrupted-images/shruti-badgainya
Keyword :
AWGN, Image Denoising, Noise, Filtering, DWT, threshold.