Image De-hazing Based on Polynomial Estimation and Steepest Descent Concept

Abstract

Digital images captured in hazy conditions suffer from colour distortion and loss of contrast, posing difficulties in being applied for further applications. Due to the existed challenge and its great significance, a large amount of research has been conducted for image de-hazing. Among the image haze removal methods, the algorithm based on dark channel prior is proved to be the most effective. Furthermore, the introduction of guided filter has boosted its efficiency to a large extent. However, the requirement for transmission refinement and the assumption that the transmission is the same in each colour channel still make the DCP concept based methods time consuming and suffer from colour distortion. To solve this problem, an approach named as Image De-hazing Based on Polynomial Estimation and Steepest Descent Concept (IDBPESDC) is proposed, which derives the pixel-wised transmission that does not require any further refinement. Additionally, image de-hazing procedures based on the steepest descent concept are adopted so that the objective of saturation enhancement under the minimum hue change constraint is achieved. Experiments are conducted on one hundred hazy images, processed by the proposed method and four other available approaches. Results are analysed qualitatively and quantitatively, which verified the effectiveness and efficiency of the proposed algorithm.