一种优化的灰度图像压缩算法  

An Optimized Gray-Scale Image Compression Algorithm

作　　者：王炳月 贾连印[1] 范瑶 孙劭文 WANG Bingyue;JIA Lianyin;FAN Yao;SUN Shaowen(School of information engineering and automation,Kunming university of science and technology,Kunming 650500,China)

机构地区：[1]昆明理工大学信息工程与自动化学院,云南昆明650500

出　　处：《电视技术》2022年第5期17-23,共7页Video Engineering

基　　金：国家自然科学基金(No.11961141001),国家自然科学基金(No.U1831204)。

摘　　要：在保证压缩率和压缩质量的前提下提高压缩速度,是图像压缩要解决的重要问题。传统的Kamata灰度图像压缩算法具有较高的图像压缩质量,但其存在Hilbert扫描效率低及需分区后合并的不足,导致压缩效率降低。为此,设计高效灰度图像压缩算法FZF-MIP,引入高效的Hilbert解码算法,避免对具有特定前缀的输入数据进行解码,从而大幅提高Hilbert扫描效率。此外,设计高效的分区中合并策略,使得小分区的合并可在分区中统一进行,避免分区后合并的额外的时间和空间开销。实验结果表明,提出的图像压缩算法可将Kamata算法的压缩和解压效率分别提升37.8%和42.4%。Improving compression speed while keeping compression quality and ratio is an open problem.The traditional Kamata algorithm suffers from large Hilbert scan time and partition merging operations,resulting in a low compression efficiency.To this end,this paper designs an efficient gray image compression algorithm FZF-MIP,which introduces an efficient Hilbert decoding algorithm that can avoid decoding input data with a specific prefix,thus leading to a high Hilbert scan efficiency.Besides,FZF-MIP further designs an efficient merge-in-partition strategy,which merges small partitions in the partitioning process,thus additional time and space overheadscan be avoided.Results show that FZF-MIP can increase the compression and decompression efficiency by 37.8%and 42.4%,respectively,compared with Kamata’s algorithm.

关 键 词：图像压缩 HILBERT扫描 分区中合并 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]