A New Technique for Lossless Compression of Color Images Based on Hierarchical Prediction, Inversion and Context Adaptive Coding

B. Koc, Z. Arnavut, D. Sarkar, H. Kocak
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引用次数: 1

Abstract

This work introduces a new technique for lossless compression of color images. The technique is composed of first transforming an RGB image into luminance and chrominance domain (Y CuCv). Then, the luminance channel Y is compressed with a context-based, adaptive, lossless image coding technique (CALIC). After processing the chrominance channels with a hierarchical prediction technique that was introduced by Kim and Cho, Burrows-Wheeler Inversion Coder (BWIC) or JPEG 2000 is used to compress of the chrominance channels Cu and Cv. It is demonstrated that, on a wide variety of images, particularly on medical images, the technique achieves substantial compression gains over other well-known compression schemes such as CALIC, JPEG 2000, LOCO-I, BPG(HEVC), and the previously proposed hierarchical prediction and context adaptive coding technique LCIC.
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基于分层预测、反演和上下文自适应编码的彩色图像无损压缩新技术
本文介绍了一种彩色图像无损压缩的新技术。该技术首先将RGB图像转换为亮度和色度域(ycucv)。然后,使用基于上下文的自适应无损图像编码技术(CALIC)对亮度通道Y进行压缩。在使用Kim和Cho引入的分层预测技术处理色度通道后,使用Burrows-Wheeler反转编码器(BWIC)或JPEG 2000压缩色度通道Cu和Cv。研究表明,在各种各样的图像上,特别是在医学图像上,该技术比其他知名的压缩方案(如CALIC、JPEG 2000、LOCO-I、BPG(HEVC)和先前提出的分层预测和上下文自适应编码技术LCIC)实现了显著的压缩增益。
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