关键词: 图像融合, 金字塔变换, 显著性检测

Abstract: This paper presents a novel strategy for image fusion by simulating visual attention mechanism. Firstly, source image is decomposed to low and high frequency components by Laplacian pyramid method. Then different frequency level is fused with different fusion rules. The fused pixels in low frequency component are chosen based on the rule of maximum saliency. And those pixels in high frequency component are chosen by the rule of weighted average based on correlation. The final fused image is reconstructed by Laplacian pyramid transform. Since pyramid transform can provide the multi-resolution of image, but cannot distinguish the importance of pixel in the image, while the saliency detection can locate the saliency region in image, but very sensitive to the noise. Combining those two algorithms may complement each other and bring benefits. The experimental results show that the performance of the proposed method is better than that of other published pyramid transform based fusion algorithms. It can be utilized to multi-focus image fusion, multiband image fusion and multispectral image fusion cases.

Key words: image fusion, pyramid transform, saliency detection