Multiresolution Color-Scale Morphological Filtering Based On Max Lift Scheme

Mathematical morphology (MM) or simply morphology can be defined as a theory for the analysis of spatial structures. It is called morphological because it aims at analyzing the shape and form of objects. It is mathematical in the sense that the analysis is based on set theory, integral geometry, and lattice algebra. The solution to some practical problems led G Matheron and J. Serra to make the solid foundation of the binary mathematical morphology and the grayscale mathematical morphology, and then the theory spurted out more power to resolve much more new questions. Because we live in a colorful nature, it is important for us to develop the color-scale mathematical morphology to processing color pictures;In the other way, Lift Scheme, the second generation wavelets recently proposed by Swesdens, is a useful technique for constructing new wavelet decomposition. The basic idea, as its name, is to start with a simple or trivial multiresolution analysis, and gradually work one's way up to a multiresolution analysis with particular properties. So the lifting scheme allows one to custom-design the nonlinear filter, needed in the transform algorithms, to the situation at hand.In this thesis some nonlinear color-scale morphological filter are designed to filter some noised color images and detect the color edge of image based on Max Lift Decomposition Scheme. And the performance index is presented, which implies that the new color-scale morphological filter has better performance.