Ultra-Low Rate Progressive Coding of Images

用于渐进图像压缩的算法寻求以这样一种方式表示图像，即数据文件的一小部分可以允许显示的图像是可识别的，并且数据的较大部分允许改进的图像质量。渐进式图像压缩的主要应用是远程数据库浏览、Internet图像跳转和需要扫描大量图像的快速远程决策任务。目标是将图像压缩到“刚刚可识别”的质量。然后，用户可以利用仅可识别的图像，同时逐步扫描图像数据库，只要确定不是所寻找的图像，就“退出”每个图像。本研究涉及有和无信道噪声的超低速率渐进图像编码的理论理解，以及低带宽视频压缩和分组网络图像传输等应用的实用算法的开发和评估。本研究的一部分侧重于算法开发，包括小波零树编码的超低率优化，以及使用区域或线漫画编码。研究人员正在研究信道噪声对渐进编码系统的影响，并正在开发灰度和彩色位渐进图像编码算法，这些算法在信道噪声存在时不会表现出灾难性的崩溃。一种有前途的方法是将速率兼容的穿孔卷积码应用于用小波零树方法压缩的图像。人类观察者对渐进式图像编码器的反应时间的实验研究将使研究人员能够定量地比较一种渐进式图像编码器与另一种图像编码器，并深入了解人类对刚刚可识别的图像的感知反应。

Algorithms for progressive image compression seek to represent an image in such a way that a small fraction of the data file can allow a displayed image to be recognizable, and a larger portion of the data allows improved image quality. The main applications of progressive image compression are for browsing of remote databases, Internet image hopping, and fast remote decision-making tasks where many images must be scanned. The goal is to compress images to rates so low as to yield "just-recognizable" quality. The user can then exploit just- recognizable images while progressively scanning an image database by "quitting" each image as soon as it is determined not to be the one sought. This research involves theoretical understanding of ultra-low rate progressive image coding both with and without channel noise, as well as the development and evaluation of practical algorithms for applications such as low-bandwidth video compression and packet network image transmission. One portion of this research focuses on algorithm development, including optimization of wavelet zerotree coding for ultra-low rates, and coding using regions or line caricatures. The investigators are studying the effect of channel noise on progressive coding systems, and are developing both grayscale and color bit progressive image coding algorithms that do not exhibit catastrophic breakdown in the presence of channel noise. One promising approach uses rate compatible punctured convolution codes applied to images compressed with a wavelet zerotree method. Experimental studies of response times for human observers of progressive image coders will allow the researchers to quantitatively compare one progressive image coder against another, and yield insight into human perceptual responses to just-recognizable imagery.