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Objective Quality Assessment in Color Image Denoising: New Tools and Validation Procedures

机译:客观质量评估彩色图像去噪:新工具和验证程序

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Color image denoising is a very difficult task because color distortion and detail blur should be avoided during noise removal. Current metrics address only a subset of filtering features that should be considered to really assess the quality of a filtered picture. In order to address this issue, a new method for objective quality assessment of filtered images is presented in this paper. The proposed approach operates in the YC_bC_r color coordinate system and is based on the decomposition of the mean squared error (MSE) into six different components. Each component considers a different class of filtering errors affecting the luminance or chroma channels of the denoised picture. Results of computer simulations dealing with color images corrupted by Gaussian and impulse noise show that the proposed approach is effective and can estimate the exact distributions of residual noise, color distortion and detail blur, whereas other metrics cannot.
机译:彩色图像去噪是一项非常艰巨的任务,因为在噪声拆除期间应避免彩色失真和细节模糊。当前的指标仅解决了应考虑的过滤功能的子集真实地评估过滤图片的质量。为了解决这个问题,本文提出了一种用于滤波图像的客观质量评估的新方法。所提出的方法在YC_BC_R颜色坐标系中运行,基于平均平方误差(MSE)分解成六个不同的组件。每个组件考虑影响Denoised图片的亮度或色度通道的不同类别的过滤误差。通过高斯和脉冲噪声损坏的计算机模拟的结果表明,所提出的方法是有效的,可以估计残留噪声,颜色失真和细节模糊的精确分布,而其他度量不能估算。

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