Points on the RD-Curve

[rastaman7]

Hello, If possible, could you provide us the points(the value of x and y axis) on the RD-Curve "Figure 4. (b) Comparison on Kodak image set" on the paper? I would like to use them for comparison with other methods.

[huzi96]

Sure: bpp - PSNR 0.2072 30.0631 0.2694 31.0654 0.3082 31.6113 0.3629 32.2974 0.4102 32.8406 0.4508 33.2612 0.4898 33.6535 0.7951 36.2269 1.0593 38.0253 1.2171 38.8963

bpp - MS-SSIM 0.2783 0.9771 0.4294 0.9860 0.5609 0.9897 0.6692 0.9919 0.7414 0.9928 0.8733 0.9942 1.2003 0.9962 1.4362 0.9971 1.5593 0.9975

Note that all average PSNR (MS-SSIM) values are calculated by computing an arithmetic mean over the PSNR (MS-SSIM) of all instances of images (24 images in total)

[rastaman7]

Thank you so much for the prompt reply.

[mosquitobite]

@huzi96 @rastaman7 Thanks for your data! Could you additionally provide us the points on the RD-Curve "Figure 4. (c) Comparison on Tecnick image set" on the paper?

[guoguo1314]

您好，能顺便给给clic数据集的点？谢谢哈！！

[huzi96]

Results on CLIC dataset (note that this is combining the mobile and professional set):

bpp - PSNR [ 0.19384457, 32.99371085], [ 0.21904684, 33.45755274], [ 0.28536838, 34.49140415], [ 0.55464888, 37.26209035], [ 0.74801618, 38.76311242], [ 0.87741394, 39.55085301], [ 1.05560752, 40.59231226]

bpp - MS-SSIM [ 0.22165698, 0.97834674], [ 0.35615207, 0.98562604], [ 0.47793141, 0.98901668], [ 0.62259978, 0.99193628], [ 0.74096972, 0.99329743], [ 1.03776218, 0.99555306], [ 1.25181141, 0.99649041], [ 1.36933935, 0.99696643]

[guoguo1314]

好的，谢谢哥，祝你天天开心！！！aha

[guoguo1314]

突然发现你clic不是我想要的clic，我想要的是clic professional_valid_2020，里面有41张图那个，你代码我有点看不懂，所以不知道怎么测试。

[huzi96]

我帮你测，晚些时候给你结果

[guoguo1314]

好的，哥，祝你生十个大胖儿子

[huzi96]

Here you go: Results on the 202 clic professional validation set (41 pics) bpp - PSNR [0.15360859, 34.11235228], [0.22438802, 34.83270459], [0.29442757, 35.46279542], [0.5779806 , 37.4223737 ], [0.78131466, 38.7738495 ], [0.91276244, 39.50645024], [1.09498735, 40.48299149]

bpp - MS-SSIM [0.21494572, 0.97588244], [0.33995646, 0.98372149], [0.45261555, 0.98762547], [0.60432187, 0.99146225], [0.72509949, 0.99313321], [1.03220965, 0.99608075], [1.25310281, 0.99728458], [1.37180624, 0.99779866]]

[guoguo1314]

Here you go: Results on the 202 clic professional validation set (41 pics) bpp - PSNR [0.15360859, 34.11235228], [0.22438802, 34.83270459], [0.29442757, 35.46279542], [0.5779806 , 37.4223737 ], [0.78131466, 38.7738495 ], [0.91276244, 39.50645024], [1.09498735, 40.48299149]

bpp - MS-SSIM [0.21494572, 0.97588244], [0.33995646, 0.98372149], [0.45261555, 0.98762547], [0.60432187, 0.99146225], [0.72509949, 0.99313321], [1.03220965, 0.99608075], [1.25310281, 0.99728458], [1.37180624, 0.99779866]]

好的，谢谢哥，晚安诺

[guoguo1314]

学长，我有个疑问。我发现在High-Efficiency Lossy Image Coding Through Adaptive Neighborhood Information Aggregation的fig6 c您的是比cheng2020低的，如果是按照上面数据画出来的话是比cheng2020高了；第一个点，如果是0.15bpp，psnr是34.112，从这张图看是太强了。 数据集：https://data.vision.ee.ethz.ch/cvl/clic/professional_valid_2020.zip

[huzi96]

啊我PSNR算错了，重跑一下，稍等

[guoguo1314]

哈哈，麻烦学长了。手动狗头！

[huzi96]

Here you go: bpp-PSNR [0.15360859, 31.88385511], [0.22438802, 33.26235119], [0.29442757, 34.33872525], [0.5779806 , 37.17813974], [0.78131466, 38.69458373], [0.91276244, 39.46479383], [1.09498735, 40.46452185]

bpp-MS-SSIM [0.21494572, 0.97588244], [0.33995646, 0.98372149], [0.45261555, 0.98762547], [0.60432187, 0.99146225], [0.72509949, 0.99313321], [1.03220965, 0.99608075], [1.25310281, 0.99728458], [1.37180624, 0.99779866]

[guoguo1314]

好的，谢谢学长，祝你生活开心！！！