Image Hybrid Filtering Based On Triangle Module Fusion Criterion

Image filtering plays a very important role in image processing. The quality of the image filtered will influence the quality of later process such as edge detection, image segmentation, feature extraction, pattern recognition and so on straightly. Image filter is expected to both reduce the noise and keep the image details. But it is difficult to design such a good filter for the overlapping of noise and image details. So image filtering is still a very important and hot research field in image processing.In this dissertation, a new hybrid filter algorithm based on triangle module fusion operator is proposed to overcome the shortcoming of conventional linear and nonlinear filter technology. Based on research and academic analysis of information fusion technology, the dissertation brings forward the idea of triangle module operator and its algorithm in order to avoid the defect caused by the judgment of the edge points with a single criterion. The new triangle module operator algorithm is implemented in a linear and non-linear hybrid filer, and the simulation results are shown to verify its good performance. Finally, some pieces of advice on how to improve the performance of the hybrid filter based on information fusion are given.The algorithm of hybrid filter based on triangle module operator may fuse different criterions in judgment level to get the best criterion. It effectively reduces the error probability and gives a new research direction for image filtering.