A New Quality Assessment Index for Compressed RS Image
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Abstract
Quality assessment for remote sensing image compression is of great significance in many practical applications. A muti-dimensional structure model is 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 index-Q is proposed and validated through a series of experiments. The experiments show that Q has a better consistency with subjective assessment results than conventional PSNR.
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