Image de-noising and enhancement based on rough set and principal component analysis

In this paper, we conduct research on novel image de-noising and enhancement algorithm based on rough set theory and the principal component analysis. Mathematically, image de-noising belongs to ill-posed inverse problem an effective way to solve the discomfort of basic qualitative is introducing a priori information about the image in image processing as the image de-noising is transformed into the well-posed problem. Under this guidance, we propose the novel perspective on the set theory and the principal component analysis based methodology. In the future research, we will integrate the experimental analysis for further optimization.