Using saliency detection to improve multi-focus image fusion

In this paper, we introduce a novel and efficient algorithm based on saliency detection methods, our main contribution is a new manner to calculate the weight map by normalising the saliency values obtained from the input images, which makes it possible to differentiate the focused and defocused regions. We have experiment three techniques of computing the weight map using contourlet transform and low-rank and structured sparse matrix decomposition (LSMD) model. The performance of the proposed model is compared with that of the state-of-the-art multi-focus fusion methods by using fusion metrics. Our evaluation of a series of dataset image demonstrate that the proposed method provides an improvement both visual quality and objective assessment compared to existing methods.