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JPEG vs. JPEG2000: An Objective Comparison of Image Encoding Quality

机译:JPEG与JPEG2000:图像编码质量的客观比较

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This paper describes an objective comparison of the image quality of different encoders. Our approach is based on estimating the visual impact of compression artifacts on perceived quality. We present a tool that measures these artifacts in an image and uses them to compute a prediction of the Mean Opinion Score (MOS) obtained in subjective experiments. We show that the MOS predictions by our proposed tool are a better indicator of perceived image quality than PSNR, especially for highly compressed images. For the encoder comparison, we compress a set of 29 test images with two JPEG encoders (Adobe Photoshop and Irfan View) and three JPEG2000 encoders (JasPer, Kakadu, and IrfanView) at various compression ratios. We compute blockiness, blur, and MOS predictions as well as PSNR of the compressed images. Our results show that the IrfanView JPEG encoder produces consistently better images than the Adobe Photoshop JPEG encoder at the same data rate. The differences between the JPEG2000 encoders in our test are less pronounced; JasPer comes out as the best codec, closely followed by IrfanView and Kakadu. Comparing the JPEG- and JPEG2000-encoding quality of IrfanView, we find that JPEG has a slight edge at low compression ratios, while JPEG2000 is the clear winner at medium and high compression ratios.
机译:本文描述了不同编码器图像质量的客观比较。我们的方法基于估计压缩伪影对感知质量的视觉影响。我们提出了一种工具,可以测量图像中的这些伪像,并使用它们来计算对主观实验中获得的平均意见得分(MOS)的预测。我们表明,我们提出的工具进行的MOS预测比PSNR更好地指示了感知的图像质量,特别是对于高度压缩的图像。为了进行编码器比较,我们使用两个JPEG编码器(Adobe Photoshop和Irfan View)和三个JPEG2000编码器(JasPer,Kakadu和IrfanView)以各种压缩率压缩一组29张测试图像。我们计算块状,模糊和MOS预测以及压缩图像的PSNR。我们的结果表明,在相同数据速率下,IrfanView JPEG编码器产生的图像始终比Adobe Photoshop JPEG编码器更好。在我们的测试中,JPEG2000编码器之间的差异不太明显。 JasPer成为最佳编解码器,紧随其后的是IrfanView和Kakadu。比较IrfanView的JPEG和JPEG2000编码质量,我们发现JPEG在低压缩率下具有轻微的优势,而JPEG2000在中等和高压缩率下显然是赢家。

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