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A No-Reference Remote Sensing Image Quality Assessment Method Using Visual Information Fidelity Index

机译:使用视觉信息保真索引的无参考遥感图像质量评估方法

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A novel image quality assessment method for remote sensing image is presented in the paper. Blur and noise are two common distortion factors that affect remote sensing image quality. Those two factors influence each other in both space and frequency domain. So it is difficult to objectively evaluate remote sensing image quality while exist these two kinds of distortion simultaneously. In the proposed method, the input image is first re-blurred by Gaussian blur kernels and also re-noised by white Gaussian noise. Then we measure the amount of mutual information loss before and after image filtering and noising. We take the VIF index as a measure of the information loss. The proposed method does not require reference image and can estimate distorted image with both blur and noise. Experimental results of the proposed method compared with other full-reference methods are presented. It is an accurate and reliable no-reference remote sensing image quality assessment method.
机译:纸张中提出了一种用于遥感图像的新型图像质量评估方法。模糊和噪声是两个影响遥感图像质量的常见失真因子。这两个因素在空间和频域中互相影响。因此,难以客观地评估遥感图像质量,同时存在这两种失真。在该方法中,输入图像首先由高斯模糊内核重新模糊,也通过白色高斯噪声重新发出。然后我们测量图像过滤和通知前后的相互信息丢失量。我们将VIF指数作为信息丢失的衡量标准。所提出的方法不需要参考图像,并且可以用模糊和噪声估计扭曲图像。提出了该方法的实验结果与其他全参考方法相比。它是一种准确可靠的无参考遥感图像质量评估方法。

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