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Haze removal for a single visible remote sensing image

机译:去除单个可见遥感影像的雾霾

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Satellite remote sensing image often suffers from haze degradation, which deteriorates significantly the effect of data intelligibility and interpretability. Hence, haze removal technique is essential for inferring high quality images with clear visibility to improve the application value of the satellite images. Thin haze removal is a challenging task since the estimation of haze component is easily affected by ground features. To solve the problem, this paper develops an effective haze removal method for a single visible remote sensing image. Firstly, haze is considered as an additive contamination and can be represented by a haze thickness map (HTM). A ground radiance suppressed HTM (GRS-HTM) is then proposed for a more precise estimation of haze distribution. The haze component for each band is calculated via GRS-HTM and can be removed to recover the clear image. Several visible satellite images with different resolutions were tested to validate the effectiveness of the proposed method. The evaluation results with qualitative and quantitative assessments demonstrate that the proposed method is superior to the traditional methods, and can recover a haze-free image with high quality.
机译:卫星遥感图像经常遭受雾度下降,这严重恶化了数据清晰度和可解释性的影响。因此,除雾技术对于推断清晰可见的高质量图像至关重要,以提高卫星图像的应用价值。薄雾霾去除是一项艰巨的任务,因为雾霾分量的估算很容易受到地面特征的影响。为了解决该问题,本文针对单个可见遥感图像开发了一种有效的除雾方法。首先,雾度被认为是添加剂污染,可以用雾度厚度图(HTM)表示。然后提出了抑制地面辐射的HTM(GRS-HTM),以更精确地估算雾度分布。每个波段的雾度分量都是通过GRS-HTM计算得出的,可以删除以恢复清晰的图像。测试了几个具有不同分辨率的可见卫星图像,以验证所提出方法的有效性。定性和定量评估的评估结果表明,所提出的方法优于传统方法,并且可以恢复高质量的无雾图像。

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