A Novel Reduced Reference Image Quality Analysis M
2016-08-23
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In this article, a novel metric for Reduced Reference Image Quality Analysis is presented which significantly reduces the amount of data required to be captured from the reference image in order to assess the quality of the distorted image.
The key concept here is to determine the quality of a distorted image from the number of connected components in the image. Comparative results indicate that the proposed metric offers reasonable accuracy. It implies that the human visual system is able to detect the reduction in number of connected components in images when using higher compression ratio with JPEG compression scheme. The proposed method also introduces efficiency by reducing the RR data rate requirement to one third of that of the existing best metric. As future work, the proposed RR IQA metric can be extended to determine the image quality for additional types of distortions applied to images.
The key concept here is to determine the quality of a distorted image from the number of connected components in the image. Comparative results indicate that the proposed metric offers reasonable accuracy. It implies that the human visual system is able to detect the reduction in number of connected components in images when using higher compression ratio with JPEG compression scheme. The proposed method also introduces efficiency by reducing the RR data rate requirement to one third of that of the existing best metric. As future work, the proposed RR IQA metric can be extended to determine the image quality for additional types of distortions applied to images.
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