A comparison of criterion functions for fusion of multi-focus noisy images

In many practical applications, images are distorted by impulsive noise (IN) produced by image sensors and/or communication channels. This noise may cause miscalculation of sharpness values which, in turn, introduce significant errors in the results of image fusion. In this paper, conventional focus measures and frequency selective weighted median filter (FSWM) are evaluated for fusion of multi-focus images in the presence of IN. FSWM is also compared with other multi-focus fusion methods such as Laplacian Pyramid and wavelet. Experimental results are presented for several sets of images and the results show that FSWM can provide better performance than other focus measures and methods.