An Image Dehazing Approach With Adaptive Color Constancy for Poor Visible Conditions

The presence of suspended particles in turbid media not only superimposes a veil on the scene but also changes the color of the scene, resulting in poor visibility and low contrast of images. It is essential to overcome these effects for further applications of the images. However, these effects are difficult to eliminate simultaneously and thus the restoration for the images becomes multitasked. In this letter, we propose an extended image formation model that introduces color constancy theory to discuss the change of light color when natural light penetrates the medium to the object. Based on the model, the image restoration task is divided into two parts: dehazing and color correction, and for these two parts, scene depth fusion-based dehazing and adaptive color constancy are proposed. The dehazing approach introduces a weighted fusion strategy to estimate scene depth to achieve a better dehazing effect. The color constancy approach improves the Gray World hypothesis with gain factors to adaptively compensate for the chromatic loss and extends the color deviation solved by color constancy from color temperature to medium. Extensive experiments on images of different scenes prove the effectiveness of the proposed method in image restoration.