A novel algorithm of image denoising based on the grey absolute relational analysis

The paper presents a novel image denoising algorithm based on grey absolute relational analysis of grey system theory. The time of applying grey system theory into noise reduction is not very long, and there are some imperfections left to be improved. We analyze the classic filter based on the grey relational analysis, and propose a novel approach to design the reference sequence, which may be much closer to the true value of the central pixel in the window. Note that there is noise whose value is not very little existing in the filter window around the central pixel, and we improve the decision-making method of grey absolute relational coefficients which are the weights of each pixel in the window. The final procedure of measures we have taken is to adopt the continuity in time and direction or position among the image pixels between the last filter window and the next one, which can decrease noise in the neighborhoods of the filter window. Compared with other popular filters, such as the traditional mean filter, the median filter, and the adaptive added-weigh mean filter based on the grey relational degree, the experimental results show that our method is more effective and feasible as it can keep the details of images while eliminating the noise.