The Research On Methods Of Muti-fous Image Fusion

With the development of imaging sensors, more and more digital image processing technologies are applied to some fields. It is difficult or impossible to make all the objects focused in the same scene. It can be solved by multi-focus image fusion. The technology has attracted more and more attention in recent years, it is widely used in these areas such as machine vision, digital camera and object recognition and so on. This paper studies the theories about wavelet analysis and multi-focus image fusion, and proposed two fusion algorithm based on local activity and adaptive partition.First, wavelet transform theories are systematically reviewed and summarized from the point of view of signal and information processing. The characteristic of each algorithm and wavelet transform is analyzed theoretically. According to this analysis, a multi-focus image fusion algorithm based on wavelet transform and local activity is proposed, the multi-focus images were decomposed by the wavelet transform. Then the high frequency coefficients of each direction were fused according to local activity rule. its performance is tested to be superior to the congener algorithms. By in-depth research of characteristics of multi-focus image and its definition and each algorithm, a multi-focus image fusion algorithm based on adaptive partition is proposed. Because boundary areas was more partitioned, the three areas was partitioned more accurately. Its performance is tested to be superior to the congeneric algorithms and the algorithm based on wavelet transform.