EAGL: Enhancement Algorithm based on Gamma Correction for Low Visibility Images

Abstract

Under poor light conditions or improper acquisition settings, the image degrades due to low contrast, poor brightness and suffer poor visual quality of the picture. An enhancement is required to manipulate the scale of pixel intensity for significant improvement in the image. This paper proposed the method of gamma correction with a self-adaptive value in accordance with the intensity scale of the image. After transformation to HSI (hue, saturation and intensity) channel, a multi-scale wavelet transform is implemented on the intensity component of the image. The gamma scale is computed from the combination of reformed scale constant of logarithm function and Minkowski distance measure. Lastly, wavelet based denoising technique is applied to suppress high noise coefficients to improve quality of the image. The proposed method is evaluated in terms of visual appearance, measure of information content, signal to noise ratio, and universal image quality index. It demonstrated that the proposed method showed its efficacy in terms of quality and improved visibility.