Selective Neighbouring Wavelet Coefficients Approach for Image Denoising

SELECTIVE NEIGHBOURING WAVELET COEFFICIENTS APPROACH FOR IMAGE DENOISING B. Chinna Rao1, M. Madhavi Latha2 1 Department of ECE, RK College of Engineering, Vijayawada, A.P., India, E-mail: [email protected]. 2 Department of ECE, Jntu College of Engineering, Hyderabad, A.P., India, E-mail: [email protected]. The denoising of a natural image corrupted by Gaussian noise is a classical problem in signal or image processing. G.Y. Chen, Donoho and his coworkers at Stanford pioneered a wavelet denoising scheme by thresholding the wavelet coefficients arising from the standard discrete wavelet transform. This work has been widely used in science and engineering applications. However, this denoising scheme tends to kill too many wavelet coefficients that might contain useful image information. In this paper, we propose one selective approach wavelet image thresholding scheme by incorporating neighbouring coefficients, namely Selected NeighShrink. This approach is valid because a large wavelet coefficient will probably have large wavelet coefficients as its neighbours. We selected the neighbours based on the directions. Here we selected widow size 3 × 3 to get better results.