Fast and Efficient Algorithm to Remove Gaussian Noise in Digital Images
V. R. Vijaykumar, Ponnusamy Thangapandian Vanathi, Pradeep Mohan Kumar Kanagasabapathy · 2010
In this paper, a new fast and efficient algorithm capable in removing Gaussian noise with less computational complexity is presented. The algorithm initially estimates the amount of noise corruption from the noise corrupted image. In the second stage, the center pixel is replaced by the mean value of the some of the surrounding pixels based on a threshold value. Noise removing with edge preservation and computational complexity are two conflicting parameters. The proposed method is an optimum solution for these requirements. The performance of the algorithm is tested and compared with standard mean filter, wiener filter, alpha trimmed mean filter K- means filter, bilateral filter and recently proposed trilateral filter. Experimental results show the superior performance of the proposed filtering algorithm compared to the other standard algorithms in terms of both subjective and objective evaluations. The proposed method removes Gaussian noise and the edges are better preserved with less computational complexity and this aspect makes it easy to implement in hardware.