Wu Xiaolin, Zhang Xiangjun, Wang Xiaohan
Department of Electrical and Computer Engineering, McMaster Univeristy, ON, Canada.
IEEE Trans Image Process. 2009 Mar;18(3):552-61. doi: 10.1109/TIP.2008.2010638.
Recently, many researchers started to challenge a long-standing practice of digital photography: oversampling followed by compression and pursuing more intelligent sparse sampling techniques. In this paper, we propose a practical approach of uniform down sampling in image space and yet making the sampling adaptive by spatially varying, directional low-pass prefiltering. The resulting down-sampled prefiltered image remains a conventional square sample grid, and, thus, it can be compressed and transmitted without any change to current image coding standards and systems. The decoder first decompresses the low-resolution image and then upconverts it to the original resolution in a constrained least squares restoration process, using a 2-D piecewise autoregressive model and the knowledge of directional low-pass prefiltering. The proposed compression approach of collaborative adaptive down-sampling and upconversion (CADU) outperforms JPEG 2000 in PSNR measure at low to medium bit rates and achieves superior visual quality, as well. The superior low bit-rate performance of the CADU approach seems to suggest that oversampling not only wastes hardware resources and energy, and it could be counterproductive to image quality given a tight bit budget.
最近，许多研究人员开始质疑数字摄影中一种长期存在的做法：过采样后进行压缩，并寻求更智能的稀疏采样技术。在本文中，我们提出了一种在图像空间中进行均匀下采样的实用方法，通过空间变化的方向低通预滤波使采样具有适应性。所得的下采样预滤波图像仍保持传统的方形采样网格，因此，可以在不改变当前图像编码标准和系统的情况下进行压缩和传输。解码器首先对低分辨率图像进行解压缩，然后在约束最小二乘恢复过程中，使用二维分段自回归模型和方向低通预滤波的知识将其向上转换为原始分辨率。所提出的协作自适应下采样和上转换（CADU）压缩方法在低到中等比特率下的PSNR测量中优于JPEG 2000，并且在视觉质量上也更胜一筹。CADU方法卓越的低比特率性能似乎表明，过采样不仅浪费硬件资源和能量，而且在比特预算紧张的情况下，可能会对图像质量产生适得其反的效果。
