Application Of Image Morphology And Wavelets In Image Enhancement And Edge Detection

Image engineering can be arranged into three catalogs according to class in term of research approach and nonfigurative degree, namely image engineering is combination of image processing, image analysis and image understanding and their engineering application. Image enhancement and edge detection is attached importance to image processing reaearch. Image target detection belongs to image analysis and its engineering application.Mathematics morphology is based on set theory, which is a powerful approach in geometrical description and nonlinear filtering. Wavelet analysis is result of development of functional analysis and numerical analysis and so on, which is a main implement or tool applied in computer vision, pattern recognition, signal and image processing.The research in this paper including noise image enhancement and edge detection relates to image processing, image analysis and their engineering application, which is application of image morphology and wavelet in image engineering.(1) According to correlative conception of parallel multiplex order morphology transformation, non-linear filter is constructed to remove high frequence noise of image such as noise of Gaussian and impulse. Within this algorithm, the local weighted mean value filtering is performed to obtain basic value of image enhancement; Structuring elements of different direction are used to match edge of image. Weighted average values about structuring elements of different direction are calculated to distinguish edge and reject noise; The difference between the maximum among these weighted average values and basic value above is served as enhancement value for enlarging dynamic scope of image gradient; For the regions in image where gray value is high or change intensely, local mean value and variance is adopted to control enhancement coefficients. So through the algorithm, the target and edge of image are elevated while high frequence noise of image is restrained. comparison of average value, standard deviation and entropy of image between original images and their enhancement show that contrast of images is improved.(2) Based on conception and correlative properties of percentile morphology transformation, the principle of edge detection using percentile morphological filtering is illustrated. The effect of structuring elements and percentile on edge detection is discussed. Based on the idea of multi-scale morophological filtering, Three order morphological operators of edge detection are constructed by extending the basic morphological operators of edge detection to restrain noise. The specialities of the operators which were monotony about percentile (p,q) in the area of image edge is analyzed in theory. Based on above, three general order morphological edge operators are constructed and their formats are given, in which multi-structuring elements are selected to match image edge according to geometrical feature of image. The rules of how to select structuring elements and percentile are studied.(3) Specialty of convolution operation and differential operation of anti- symmetrical biorthogonal wavelet transformation are deduced and analyzed. Based on above, In term of arithmetic of wavelet decomposition presented, an new approach of multi-scale image edge...