An Infrared Image Enhancement Algorithm for Gas Leak Detecting Based on Gaussian Filtering and Adaptive Histogram Segmentation

Gas leak detection technology using infrared imaging provides significant advantages in detection range, efficiency and dynamic image visualization. Enhancing gas leak traces is essential to the performance of infrared image detection systems, as raw images tend to suffer from low contrast. However, traditional infrared image enhancement methods present drawbacks in the enhancement of gas leak traces. In this paper, a method for image enhancement using Gaussian filtering and adaptive histogram segmentation is proposed. This method consists of three steps: image layering, background and detail layer processing and image fusion output. The experimental results indicate that the proposed method obtained encouraging results in gas leak trace enhancement and de-noising. Compared with the global Adaptive Histogram Segmentation (AHS) algorithm, the performance of the proposed approach output confirmed the superiority of the proposed algorithm.