Image fusion using adaptive thresholding and cross filtering

This paper presents an algorithm for multifocus image fusion in spatial domain using adaptive thresholding and cross filtering. The basic idea is to gather edge information from the source images and then segment the source images into blocks using the soft blending technique instead of cutting it into simple blocks. The differences between the edge information from both the source images is computed and the mean of these differences is set as the adaptive threshold. The differences obtained from each block are compared with this adaptive threshold and only those blocks for which the difference exceeds the threshold are chosen and incorporated into the final fused image. A further enhancement is achieved by making this process iterative. In every next iteration, the image is divided such that each block is subdivided by twice the number of divisions used in the last iteration. Also the number of iterations is fixed to 100. The performance of this method has been tested on many pairs of multifocus images and has shown promising results on comparison with existing methods.