A multi-threshold adaptive filtering for image enhancement

There is a compromise between noise removal and texture preservation in image enhancement. It is difficult to do an image enhancement task by using only one simple filter for a real world image which may consist of regions of various local activities. We describe a multi-threshold adaptive filter (MTA filter) for solving this problem in this paper. It uses a generalized gradient function which reflects the local contextual information as a cue to determine the nature of the filtering for each local neighborhood. In this way, several simple filters can be combined to form a more efficient and more flexible context dependent filter. As a result, specific filter is only applied to the region which is suitable for it. Thus, a balanced texture preserving and noise removal effect can be simultaneously achieved.