Infrared Image Enhancement Based on Guided Filtering and Adaptive Algorithm and Its FPGA Implementation

Abstract

Detail enhancement and noise suppression are critical to the performance of infrared imaging systems, and a method for enhancing infrared images based on guided filters is introduced in this paper. Firstly, the guidance filter and Gaussian filter are used to decompose the original infrared image into the base layer and the detail layer, and then the adaptive histogram equalization method is used to enhance the overall brightness and contrast of the base layer. For the detail layer, we will guide the filtering to obtain the gain factor through the “$3\sigma$” rule processing, on this basis, the detail gain function is constructed to apply to the processing of the detail layer, and finally the basic layer and the detail layer are fused to obtain the final result image. The proposed method is compared with six other infrared image enhancement algorithms under different data sets and analyzed using subjective and objective evaluation indicators. The experimental data show that the proposed method can effectively improve the overall contrast and local details of the image and has good scene adaptability. Finally, we transplanted the algorithm to the FPGA bottom layer for implementation, and for 640 $\times$ 512 resolution images, the final implementation effect is almost no different from that on the PC side.