低分辨人脸图像增强方法

Recently, face recognition has made great progress and many theoretical methodsand practical systems are becoming more and more perfect. But with the currentsituation of public security is becoming increasingly serious, existing face recognitionsystems due to the quality of the image, the influence of environmental change and theuncontrollable factors, mostly unable to meet the remote identification requirements. In order to solve this problem, an effective face image enhancement method is proposed in this paper: G-Log algorithm, which is based on the gamma and logarithm transformation.The G-Log algorithm can perform the following functions: 1) eliminate the influence of illumination; 2) increase image contrast and equalize histogram; 3) restore the high-frequency components and detailed information; 4) improve visual effect; 5) enhance recognition accuracy. For comparing the effects of different enhancement algorithms, all probe images are processed by different enhancement methods and identical face alignment, recognition modules. Experiment results show that G-Log method achieves the best effect both in matching accuracy and visual effect. Long-distance uncontrolled environment face recognition accuracy has been greatly improved, up to 98%, 98%, 95% for 60-, 100-, 150-meter images after processed by G-Log from original 95%, 89%, 70%.