Medium and Long Wave Infrared Image Enhancement Fusion Method Based on Edge Preserving

Medium- and long-wave infrared image fusion has problems such as overemphasizing detail retention, which often weakens the presence of thermal information, poor contrast of fused images, and large noise, so a medium- and long-wave image fusion method based on improved non-subsample shearlt transform (NSST) is proposed. Firstly, the image processing of mid-wave infrared and long-wave infrared images is carried out in a targeted manner, and the pixel values of the target and background area are adjusted by using the adaptive contrast enhancement algorithm to adjust the pixel values of the mid-wave infrared image, so as to achieve the target enhancement effect by expanding the relative pixel difference between the thermal target and the background area. Secondly, the average curvature filtering and Gaussian filtering are used to decompose the source image into detail layer, structure layer and area layer. The energy differential feature is used to guide the energy attribute fusion strategy to fuse the regional layer, the structure layer adopts the maximum fusion strategy to fuse, and the detail layer adopts the fusion strategy of directional contrast. Finally, the three levels after fusion are added to reconstruct the final fusion image. Experimental results show that the algorithm can effectively fuse mid-wave infrared and long-wave infrared images, which can not only effectively retain the mid-wave infrared thermal radiation and heat information, but also retain the edge detail expression ability in the fusion results to a large extent. It can be seen from the subjective and objective evaluation indicators that the proposed algorithm shows better fusion performance than other algorithms.