A new multi-focus image fusion technique based on variance in DCT domain

Image fusion process is defined as extracting information and specific features from multiple input images and combining them into a single image which has all essential information. Image fusion methods which have been proposed in DCT domain are very convenient and time-saving in real-time applications. The fused output image of existing methods in DCT domain has low quality due to the side effects of their algorithms. In this article, an efficient and simple image fusion method using improved variance criteria is presented. The proposed method uses sharpened input images to make a larger difference between the variance of the corresponding input image's blocks. In addition, by adjusting two threshold values for recognizing the corresponding blocks which have close variance values, the quality of the output image is enhanced significantly. The results of conducting the proposed algorithm with gray-scale multi-focus images and evaluating the performance of the proposed method in comparison with the well-known methods confirm significant improvements in the quality of the output image. Finally, we demonstrate the simplicity of applying our method on color multi-focus images.

Keywords:

multi-focus image , image fusion , sharpened images , DCT domain