Department of Telecommunication, Technical University of Denmark, DK-2800 Lyngby, Denmark.
IEEE Trans Image Process. 1999;8(5):601-13. doi: 10.1109/83.760309.
We present general and unified algorithms for lossy/lossless coding of bilevel images. The compression is realized by applying arithmetic coding to conditional probabilities. As in the current JBIG standard the conditioning may be specified by a template. For better compression, the more general free tree may be used. Loss may be introduced in a preprocess on the encoding side to increase compression. The primary algorithm is a rate-distortion controlled greedy flipping of pixels. Though being general, the algorithms are primarily aimed at material containing half-toned images as a supplement to the specialized soft pattern matching techniques that work better for text. Template based refinement coding is applied for lossy-to-lossless refinement. Introducing only a small amount of loss in half-toned test images, compression is increased by up to a factor of four compared with JBIG. Lossy, lossless, and refinement decoding speed and lossless encoding speed are less than a factor of two slower than JBIG. The (de)coding method is proposed as part of JBIG2, an emerging international standard for lossless/lossy compression of bilevel images.
我们提出了用于双层图像有损/无损编码的通用和统一算法。通过将算术编码应用于条件概率来实现压缩。与当前的 JBIG 标准一样，可以通过模板指定条件。为了更好的压缩，可以使用更通用的自由树。在编码端进行预处理可能会引入损失以增加压缩。主要算法是一种基于率失真控制的贪婪像素翻转算法。尽管是通用的，但这些算法主要针对包含半色调图像的材料，作为对专门的软模式匹配技术的补充，这些技术更适合文本。基于模板的细化编码用于有损到无损的细化。在半色调测试图像中仅引入少量损失，与 JBIG 相比，压缩增加了四倍。与 JBIG 相比，有损、无损和细化解码速度以及无损编码速度仅慢了不到两倍。该（编）解码方法被提议作为即将推出的国际双层图像无损/有损压缩标准 JBIG2 的一部分。
