Abstract—In this paper, we proposed an image noise canceller achieved by an adaptive filter in two-dimensional block processing based on the least-mean-square algorithm. In this adaptive filter, each image is processed in two phases. In the initial weight matrix decision phase, the block-by-block operations with the smaller block size of 4 × 4 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. To verify the feasibility of this approach, the simulations in the block-adaptation phase with the block sizes of 4 × 4, 8 × 8, 16 ×16, and 32 × 32 are performed. The simulation results show that this approach achieves a higher signal-to-noise ratio in each case of block size.

Index Terms—Adaptive filter, noise cancellation, least mean-square

The authors are with the Department of Electrical Engineering, National University of Kaohsiung, 81148, Kaohsiung, Taiwan (e-mail:cychen@nuk.edu.tw).

Cite: Chuen-Yau Chen, Chih-Wen Hsia, and Cheng-Yuan Lin, "TDBLMS-Based Adaptive Filter for Image SNR Enhancement," International Journal of Computer and Communication Engineering vol. 1, no. 3, pp. 218-221 , 2012.