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Shadow removal from uniform-textured images using iterative thresholding of shearlet coefficients

机译:使用小波系数的迭代阈值法从均匀纹理图像中去除阴影

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摘要

Shadows are natural phenomena that appear in images due to inconsistent illumination of the scene being captured. Recently, the need for removal of shadows from images and videos has gained wide attention due to the ill-effects of shadows on many computer vision tasks. This paper presents a novel technique to remove shadows from images with a uniform background. Initially, our method identifies the shadow and the lit regions by discarding the low-frequency image details. This is followed by an iterative procedure in which the shadow pixels to be corrected are located by eliminating the Shearlet approximation coefficients greater than a threshold. The shadow pixels identified in each iteration are corrected using a pre-computed correction factor. The shadow-corrected image is finally inpainted to generate the shadow-free output. In order to demonstrate the superior performance of the proposed method, we provide both qualitative and quantitative comparisons of the method with other state-of-the-art techniques.
机译:阴影是由于所捕获场景的照明不一致而出现在图像中的自然现象。最近,由于阴影对许多计算机视觉任务的不良影响,从图像和视频中去除阴影的需求已引起广泛关注。本文提出了一种新颖的技术,可以从背景均匀的图像中去除阴影。最初,我们的方法通过丢弃低频图像细节来识别阴影和亮区。这之后是迭代过程,其中通过消除大于阈值的Shearlet逼近系数来定位要校正的阴影像素。使用预先计算的校正因子校正在每次迭代中识别出的阴影像素。最终对经过阴影校正的图像进行修补,以生成无阴影的输出。为了证明该方法的优越性能,我们提供了该方法与其他最新技术的定性和定量比较。

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