5 September 2008 A new quality assessment index for compressed remote sensing image
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Abstract
Quality assessment for remote sensing image compression is of great significance in many practical applications. A comprehensive index based on muti-dimensional structure model was designed for image compression assessment, which consists of gray character distortion dimension, texture distortion dimension, loss of correlation dimension. Based on this model, a new comprehensive image quality index-Q was proposed. In order to assess the agreement between our comprehensive image quality index Q and human visual perception, we conducted subjective experiments in which observers ranked reconstructed images according to perceived distortion. For comparison, PSNR is introduced. The experiments showed that Q had a better consistency with subjective assessment results than conventional PSNR.
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Liang Zhai, Liang Zhai, Xinming Tang, Xinming Tang, Guo Zhang, Guo Zhang, } "A new quality assessment index for compressed remote sensing image", Proc. SPIE 7075, Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications XI, 70750K (5 September 2008); doi: 10.1117/12.798834; https://doi.org/10.1117/12.798834
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