A self-adaptive filter algorithm based on graph theory
Wang Yun-fe · Journal of Central South University(Science and Technology) · 2013
In light of the characteristics of impulse noise, a novel self-adaptive filter based on graph theory(SAFG)approach was presented. The first step of this algorithm was to identify the impulse noise nodes of image by setting global threshold; Then, each identified node was partially operated. By comparing confidence degrees of different filter windows, the size of window was self-adaptively adjusted, so the filter window for each noise node was chosen. Finally,a two-step filter strategy was adopted, maked use of the un-noise information around noise node in this confidence filter window to restore noise nodes. The results demonstrate that the filter capabilities of the proposed SAFG algorithm can not only effectively suppress the strong impulse noise disturbing, but also preserve the image details well. It is better than traditional median-filter(MF) algorithm and Wiener filter algorithm.