不同反马赛克算法的重建性能分析

Petr Dostál, M. Klima
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引用次数: 2

摘要

许多在单片相机中使用的反马赛克算法仅对以质量质量为标准的多媒体成像系统进行了感知优化。对于应用成像系统(如安全),优化标准完全不同(如字符识别),因此评级良好的算法可能不适用于安全。为了评价字符重建的性能,在合成Snellen视力表图像测试中应用了四种最先进的插值技术。之后,由观察者组对图像质量进行评估,并计算两种不同的客观质量指标(PSNR, SSIM)进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of reconstruction performance of different demosaicing algorithms
Many proposed demosaicing algorithms used in single chip cameras are perceptually optimized only for multimedia imaging system where the QoE is used as criteria of quality. Concerning applied imaging system (e.g. security) the optimization criteria are totally different (e.g. character identification) and therefore the well rated algorithms may not be suitable for security. Four state-of-art interpolation techniques have been applied on the synthetic Snellen eye chart image test in order to evaluate the performance of character reconstruction. After that the image quality has been evaluated by the group of observers and two different objective quality metrics (PSNR, SSIM) have been calculated for comparison.
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