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A New Image Quality Assessment Method Based on SSIM and TV Model

机译:基于SSIM和电视模型的新型图像质量评估方法

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In this paper, a new image quality assessment method has been proposed in which can judge the quality of images without explicit knowledge of the reference images, it is based on the SSIM(Structural Similarity) and TV(total variation) model. Firstly, add noises to distorted image to quantitatively determine, it can get the degraded image; secondly, use the improved self-adaptive gradient weights of the TV algorithms to denoising the distorted image, it can get the "fake" reference image, then use the classical SSIM methods to make reference evaluation between the distorted image and the "fake" reference image, after modified, the results is the no reference evaluating indicator. The experiment separated use the standard testing images and the degraded images from the LIVE database to make evaluate experiment, the result show that it is consistent to the result of MOS. This method is no need of reference images, it can use widely.
机译:在本文中,提出了一种新的图像质量评估方法,其中可以判断图像的质量而不明确地了解参考图像,基于SSIM(结构相似度)和电视(总变化)模型。首先,将噪声添加到扭曲图像以定量地确定,它可以获得劣化的图像;其次,使用电视算法的改进的自适应梯度权重来去噪到扭曲的图像,它可以获得“假”参考图像,然后使用经典的SSIM方法在扭曲图像和“假”参考之间进行参考评估图像,修改后,结果是NO参考评估指标。实验分离使用标准测试图像和从实时数据库中的降级图像进行评估实验,结果表明它与MOS的结果一致。该方法不需要参考图像,它可以广泛使用。

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