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