张爱华 唐晓亮 韩杰

摘  要： 为全面缩短分形图像的压缩耗时，进而提升实时重构图像的质量条件，设计一种基于稀疏分解的新型分形图像实时压缩系统。利用规范化电源模块提供分形实时串口模块与ADV212图像压缩模块所需的供应电量，在全面整合分形图像信息的同时，完成新型压缩系统的硬件运行环境搭建。在此基础上，对原图像进行稀疏分解处理，根据目的端应用需求，重构图像传输所需的码流组织，再按照图像的最终分形结果配置具体压缩参数，实现重构图像的分形编码，结合相关硬件执行结构，完成基于稀疏分解的分形图像实时压缩系统设计。对比实验结果表明，与常规图像压缩系统相比，应用分形实时压缩系统后，横向基础压缩时间缩短至6.3 s，纵向基础压缩时间缩短至4.6 s，重构图像的质量条件得到有效提升。

关键词： 分形图像压缩; 图像信息整合; 稀疏分解; 环境搭建; 重构图像分形编码; 码流传输

中图分类号： TN911.73?34; TP309                  文献标识码： A                   文章编号： 1004?373X（2020）17?0029?05

Abstract： In order to shorten the compression time of fractal images and improve the quality of real?time reconstruction images， a new real?time fractal image compression system based on sparse decomposition is designed. The standardized power supply module is used to provide the power energy required by the fractal real?time serial port module and the image compression module ADV212. The hardware operating environment of the new compression system is built while the fractal image information is fully integrated. On this basis， original image is processed with sparse decomposition. According to the application demand of the destination end， code stream organization needed for the image transmission is reconstructed， and then the specific parameters are collocated according to the final fractal compression results of the image to implement the fractal coding of the reconstructed image. The design of the real?time fractal image compression system based on sparse decomposition is completed in combination with the relevant hardware performing structure. The experimental results show that， in comparison with the conventional image compression system， the real?time fractal compression system can shorten the compression time of horizontal foundation to 6.3 s and the compression time of vertical foundation to 4.6 s， which can effectively improve the quality conditions of reconstructed images.

Keywords： fractal image compression; image information integration; sparse decomposition; environment setup; refactoring image fractal coding; code stream transmission

0  引  言

稀疏分解是一种具有约束作用的图像正交分解应用手段，同时具备基函数系的完备性和正交性，可在保持最小固有分辨率的情况下，对分形图像进行压缩分配处理。

常规图像压缩系统所应用的正交分解手段只具备特性稀疏处理能力，即在分形图像质量条件不超过60%的情况下，才能对其进行定向分解，而随着待处理图像总量的不断增加，单个图像所具备的质量条件持续增大，直至最终数量级结果[1?2]达到100%。……