Infrared image enhancement algorithm based on seagull optimized Otsu and BEEPS algorithm in NSST domain
Xin Zhang, Yu Yang, Yike Shi, Jiahao Zhang, Zefeng Zhang, Xin Wang · International Conference on Mechanical Engineering, Measurement Control, and Instrumentation · 2021
Aiming at the problems of fuzzy, noisy, and low contrast of infrared images in detection of power equipment. This paper designs an improved Otsu segmentation threshold based on seagull optimization and BEEPS filter algorithm in NSST domain. First, the original infrared image is decomposed by NSST to high and low frequency components. Low-frequency component is divided into two parts, the foreground and background, and the enhancement processing is performed separately to each part. BEEPS algorithm is used in this paper for high-frequency component processing. Finally, the processed low-frequency components and high-frequency components are subjected to NSST inverse transformation to obtain the final enhanced image. The algorithm in this paper is compared with the other three algorithms to verify its superiority: it has improved the accuracy of infrared image threshold segmentation and strengthened the depth of field, and increase the brightness of power equipment. The overall contrast of the image is enhanced and the noise part is also effectively filtered out, improving the overall visual effect of the image which is conducive to use thermal effects to determine the operating status of power equipment and the detection and fault location of thermal fault detection.