论文标题
通过超分辨率压缩无损图像
Lossless Image Compression through Super-Resolution
论文作者
论文摘要
我们引入了一种简单有效的无损图像压缩算法。我们将图像的低分辨率版本存储为原始像素，然后进行几次无损超分辨率的迭代。对于无损超分辨率，我们预测了以低分辨率输入为条件的高分辨率图像的概率，并使用熵编码来压缩该超分辨率运算符。基于超分辨率的压缩（SREC）能够在大型数据集上使用实际运行时实现最新的压缩率。代码可在https://github.com/caoscott/srec在线获得。
We introduce a simple and efficient lossless image compression algorithm. We store a low resolution version of an image as raw pixels, followed by several iterations of lossless super-resolution. For lossless super-resolution, we predict the probability of a high-resolution image, conditioned on the low-resolution input, and use entropy coding to compress this super-resolution operator. Super-Resolution based Compression (SReC) is able to achieve state-of-the-art compression rates with practical runtimes on large datasets. Code is available online at https://github.com/caoscott/SReC.
