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Image Clarification Method Based on Structure-Texture Decomposition with Texture Refinement

机译:基于结构纹理分解和纹理细化的图像澄清方法

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This paper presents a high quality and low complexity image clarification method, which restores the visibility of images captured in bad weather and poor lighting conditions. A sequential processing of conventional dehazing and backlit correction methods has a problem that textures and noises are overemphasized by the corrections. The proposed method first decomposes a captured image into two components: a structure component forming smooth regions and strong edges and a rest component for fine textures and noises. Image enhancement is conducted based on analyses of the first component, while controlling an amplification factor of the texture component. The utilization of the structure component for the enhancement enables pixel-wise corrections without local area analysis which results in lower computational cost. Experimental results demonstrate that the proposed method can successfully enhance image qualities and its computational cost is reasonable for real-time video processing.
机译:本文提出了一种高质量,低复杂度的图像澄清方法,该方法可以恢复在恶劣天气和恶劣照明条件下捕获的图像的可见性。常规的去雾和背光校正方法的顺序处理具有这样的问题,即,校正会过分强调纹理和噪声。所提出的方法首先将捕获的图像分解为两个分量:形成平滑区域和强边缘的结构分量,以及用于精细纹理和噪声的其余分量。在控制纹理成分的放大率的同时,基于对第一成分的分析来进行图像增强。利用用于增强的结构部件可以进行逐像素校正,而无需进行局部区域分析,从而降低了计算成本。实验结果表明,该方法可以成功地提高图像质量,其计算量对于实时视频处理是合理的。

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