Fusion of RGB and HSV colour space for foggy image quality enhancement

Abstract

The physical properties of water cause light-prompted degradation of foggy images. The light quickly loses intensity as it goes in the water, depending upon the shading range wavelength. Visible light is consumed at the longest wavelength first. Red and blue are the most and least absorbed, respectively. Foggy images with low contrast, are captured due to the degradation effects of the light spectrum. Therefore, valuable information from these images cannot be fully extracted for further processing. In this paper, the authors have proposed a new method to increase contrast and reduce the noise of foggy images using CLAHE (Contrast Limited Adaptive Histogram Equalization) algorithm. The proposed method fuses the modification of image histogram into two main colour models, namely, Red–Green–Blue (RGB) and Hue-Saturation-Value (HSV). In the primary stage, the CLAHE is connected just on the red part as in water, red shading is more influenced than the blue or green shading. Furthermore, in the second stage, without influencing the hue, the CLAHE is connected to saturation and value components of the HSV colour model. Finally, enhanced image has been produced using a fusion of output of primary phase and output produced in the second phase. Two parameters, namely, RMSE (Root Mean Squared Error) and the PSNR (Peak Signal to Noise Ratio) have been considered in comparing the experimental results of the proposed system with state-of-the-art work.