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DIBR synthesized image quality assessment based on morphological wavelets

机译:基于形态小波的DIBR综合图像质量评估

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Most of the Depth Image Based Rendering (DIBR) techniques produce synthesized images which contain nonuniform geometric distortions affecting edges coherency. This type of distortions are challenging for common image quality metrics. Morphological filters maintain important geometric information such as edges across different resolution levels. In this paper, morphological wavelet peak signal-to-noise ratio measure, MW-PSNR, based on morphological wavelet decomposition is proposed to tackle the evaluation of DIBR synthesized images. It is shown that MW-PSNR achieves much higher correlation with human judgment compared to the state-of-the-art image quality measures in this context.
机译:大多数基于深度图像的渲染(DIBR)技术都会生成合成图像,其中包含影响边缘相干性的不均匀几何变形。对于常见的图像质量指标而言,这种类型的失真具有挑战性。形态过滤器会保留重要的几何信息,例如不同分辨率级别的边缘。本文提出了基于形态小波分解的形态小波峰值信噪比测度MW-PSNR,以解决DIBR合成图像的评价问题。结果表明,与当前情况下的最新图像质量度量相比,MW-PSNR与人类判断具有更高的相关性。

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