关键词: 图像融合, 细节增强, 最大Shannon 熵, 滚动引导滤波

Abstract: With the change of application environment, the engineering deployment capability of most fusion algorithms for infrared and visible images is generally poor, and there are one or more problems such as insufficient target extraction, loss of details, algorithm complexity, low efficiency, and poor applicability. Aiming at the above problems, a fusion method of infrared and visible images is proposed based on improved maximum entropy algorithm (IMES) and rolling guided filter (RGF). First, the infrared target is extracted using IMES, and the visible image and infrared image are decomposed into basic layer and detail layer using the scale perception and edge preservation characteristics of RGF. Then, the base layer fusion image is obtained from the extracted infrared target and visible base layer image by the base layer fusion rules. Finally, the final fusion image is obtained from the base layer fusion image by the detail layer fusion rules. Experimental results show that the proposed algorithm has a clear target, clear texture details and rich detail information in the fused image. Moreover, the proposed algorithm is simple, efficient, and wide applicability. Compared with the other four algorithms, the proposed algorithm has advantages in both subjective and objective evaluations, and has certain engineering deployment capability.

Key words: image fusion, detail enhancement, maximum Shannon entropy, rolling guided filter