中北大学学报（自然科学版）2025，Vol.46Issue(4)：430-437,8.DOI:10.62756/jnuc.issn.1673-3193.2024.08.0022
基于内容自适应分块的眼底图像无损压缩算法
Lossless Fundus Image Compression Algorithm Based on Content Adaptive Blocking
摘要
Abstract
The sparsity and texture distribution of an image have a significant impact on its compression performance.To achieve effective compression of fundus images,this paper proposes a content adaptive block based soft compression algorithm(ABSC)based on soft compression algorithm,and improves the gradient adaptive predictor.Firstly,the image is subjected to reversible color component transformation to obtain YUV components,and then adaptive predictive encoding is applied to different components.Secondly,the Y component is differentiated into subblocks with different features based on variance,appropriate predictors are selected,and subblocks with the same continuous prediction mode are concatenated and merged to form a new set of subblocks.Finally,the corresponding predictors are selected for encoding the subblocks of the set according to the prediction mode,thus achieving adaptive block coding.The experimental results show that compared with the soft compression algorithm,the compression ratio of our algorithm on DRIVE dataset,CHASEDB1 dataset and the dataset collected by the research group is improved by 6.8%,4.3%,and 4.1%,respectively,and is superior to typical traditional lossless compression algorithms,verifying the good per-formance of the new algorithm in lossless compression of fundus images.关键词
图像无损压缩/预测器/内容自适应分块/可逆颜色分量变换/方差Key words
image lossless compression/predictor/content adaptive partitioning/reversible color compo-nent transformation/variance分类
计算机与自动化引用本文复制引用
郭亚楠,陈燕,王康谊,张权..基于内容自适应分块的眼底图像无损压缩算法[J].中北大学学报（自然科学版）,2025,46(4):430-437,8.基金项目
山西省基础研究计划项目(202103021224204) （202103021224204）
