Image Denoising Algorithm Using Adaptive Neighboring Window and Threshold Value

Image denoising is an active area of research and probably one of the most studied problems in the image processing fields. In this paper we describe a new image denoising algorithm that based on neighborhood thresholding function which takes the correlation of the magnitude of the wavelet coefficient with its neighbors into consideration to decide whether the coefficient is noisy or noise free. Accordingly, the noisy coefficient is processed with the help of the surrounding dependent wavelet coefficients information. The proposed algorithm adapts its neighboring window size and threshold value in accordance with the estimated noise level. Experimental results show that the proposed algorithm can effectively remove the image noises with very little processing time overhead as compared with the state-of-the-art denoising algorithm.