Abstract
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.
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Acknowledgments
This study was funded by National Basic Research Program of China (973 Program) under Grant 2012CB821206.
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Shao, Y., Sun, F., Li, H. (2013). A No-Reference Remote Sensing Image Quality Assessment Method Using Visual Information Fidelity Index. In: Sun, Z., Deng, Z. (eds) Proceedings of 2013 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38466-0_36
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DOI: https://doi.org/10.1007/978-3-642-38466-0_36
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