Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada.
IEEE Trans Image Process. 2012 Dec;21(12):4797-807. doi: 10.1109/TIP.2012.2202672. Epub 2012 Jun 5.
The l(∞)-constrained image coding is a technique to achieve substantially lower bit rate than strictly (mathematically) lossless image coding, while still imposing a tight error bound at each pixel. However, this technique becomes inferior in the l(2) distortion metric if the bit rate decreases further. In this paper, we propose a new soft decoding approach to reduce the l(2) distortion of l(∞)-decoded images and retain the advantages of both minmax and least-square approximations. The soft decoding is performed in a framework of image restoration that exploits the tight error bounds afforded by the l(∞)-constrained coding and employs a context modeler of quantization errors. Experimental results demonstrate that the l(∞)-constrained hard decoded images can be restored to gain more than 2 dB in peak signal-to-noise ratio PSNR, while still retaining tight error bounds on every single pixel. The new soft decoding technique can even outperform JPEG 2000 (a state-of-the-art encoder-optimized image codec) for bit rates higher than 1 bpp, a critical rate region for applications of near-lossless image compression. All the coding gains are made without increasing the encoder complexity as the heavy computations to gain coding efficiency are delegated to the decoder.
L(∞)约束图像编码是一种技术，可实现比严格（数学上）无损图像编码低得多的比特率，同时仍在每个像素处施加严格的误差限。然而，如果比特率进一步降低，该技术在 l(2)失真度量方面会变得较差。在本文中，我们提出了一种新的软解码方法来降低 l(∞)解码图像的 l(2)失真，并保留 minmax 和最小二乘逼近的优点。软解码是在图像恢复框架中执行的，该框架利用 l(∞)约束编码提供的严格误差限，并使用量化误差的上下文建模器。实验结果表明，l(∞)约束硬解码图像可以恢复，从而获得超过 2 dB 的峰值信噪比 PSNR，同时仍保持每个像素的严格误差限。对于高于 1 bpp 的比特率，新的软解码技术甚至可以优于 JPEG 2000（一种最先进的编码器优化图像编解码器），这是近无损图像压缩应用的关键速率区域。所有编码增益都是在不增加编码器复杂性的情况下实现的，因为获得编码效率的繁重计算已委托给解码器。
