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Design and evaluation of perceptual masks for wavelet image compression

机译:小波图像压缩感知掩模的设计与评估

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Transform-based image compression performance is measured quantitatively in terms of peak signal-to-noise ratio (PSNR); subjective quality is also important to evaluating performance. An image compression system that incorporates the sensitivities of the human visual system (HVS) can enhance performance. This paper develops new HVS techniques-in the form of perceptual weighting masks derived from the luminance contrast sensitivity function-and illustrates their performance for grayscale and color images using the biorthogonal 9/7 and 22/14 wavelet transforms. Performance is measured quantitatively and qualitatively using a subjective testing procedure with 15 observers. Our HVS methods improve both PSNR and subjective quality for color images; for grayscale images, PSNR values decrease and quality increases.
机译:在峰值信噪比(PSNR)方面,定量测量基于变换的图像压缩性能;主观质量对评估性能也很重要。包含人类视觉系统(HVS)的敏感性的图像压缩系统可以增强性能。本文开发了新的HVS技术 - 以亮度对比度灵敏度函数导出的感知加权掩模的形式 - 并且说明了使用双正交9/7和22/14小波变换的灰度和彩色图像的性能。使用具有15个观察者的主观测试程序定量和定性测量性能。我们的HVS方法改善PSNR和彩色图像的主观质量;对于灰度图像,PSNR值降低和质量增加。

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