Design and implementation of TDBLMS adaptive filter and comparison of PSNR values of various de-noised images

This paper is based on the compare of peak signal to noise ratio (PSNR) value of different types of noisy images. Noisy images are filtered by two dimensional block least mean square adaptive filter algorithm (TDBLMS). In this paper, adaptive filter technique apply to improve the quality of images, such as Lena image, baboon image, mammography image and ultrasound image. These images are corrupted by additive noise and multiplicative noise, like Gaussian, Poisson, Speckle etc. Proposed algorithm of an image, noise can achieved of input images by an adaptive filter. In this adaptive filter, each image is processed the block-by-block operations with the smaller block size (2×2, 4×4, 8×8 etc.) are applied to the original noisy image for getting the suitable weight matrix that will be used as the initial one for the block-adaptation phase such that a higher signal-to-noise ratio can be achieved. The simulation result shows that the quality of image is better than input image with the help of calculated PSNR values.