Directional-smoothing-model-based image denoising algorithm
Xiaoming Zhao, Yashuo Bai, Xin Liu, Miao Gao, Kun Cheng, Shengcun Ma, Lei Dong · Journal of Optical Technology · 2020
This study focuses on edge preservation and noise smoothing in the process of denoising. To achieve these two aims, the image has to be processed in such a way that the noise is removed to give people a pleasing vision without reducing the perceptibility of edges and details. In the proposed algorithm, edge orientations are taken into account by using directional templates during edge extraction. The results of convolution are adopted to control the coefficients of the corresponding denoising filter. These two steps play a leading role in guaranteeing the preservation of edges. Finally, flat regions distinguished from edges and details by local standard deviation are further operated on by incorporating the preliminary filtering result and mean filtering result to achieve better vision perception. Its great performance with lower complexity is validated by the experiential results, which provides an important opportunity for hardware implementation.