Substation Infrared Image Fuzzy Enhancement Algorithms Based on Improved Adaptive Genetic Theory
Cui Hao-yan · Gao dianya jishu · 2015
In order to enhance the visual effect of infrared image of electric power equipment in substation, to highlight the thermal anomaly area, and to help engineers analyze the faults, a fuzzy enhancement technology infrared image based on the adaptive genetic algorithm was proposed. After the wavelet transform of the infrared image, homomorphic filtering enhancement and fuzzy enhancement were processed, and the dynamic adaptive genetic algorithm was used to optimize the parameters of fuzzy method, finally, the images were reconstructed. Experimental results show that the effect of proposed method is better than enhancement homomorphic filtering, fuzzy enhancement, and fuzzy genetic algorithm, and the image contrast, resolution, and clarity can be improved by at least 12.6%, 27.7%, and 33.7% respectively. It is favorable for the maintenance of electric power equipment, especially in thermal anomaly location and fault diagnosis.