基于GPGPU的JPEG2000图像压缩方法  

JPEG2000 Image Compression Method Based on GPGPU

作　　者：李玉峰[1,2] 吴蔚[2] 王恺[2] 崔迎炜 

机构地区：[1]东南大学移动通信国家重点实验室,南京210096 [2]沈阳航空航天大学电子信息工程学院,沈阳110136 [3]北京方天长久科技有限公司,北京100085

出　　处：《电子器件》2013年第2期163-168,共6页Chinese Journal of Electron Devices

基　　金：国家自然科学基金(61171081)

摘　　要：为了进一步加快JPEG2000的压缩速度,对JPEG2000压缩标准进行研究,分析得出JPEG2000核心算法离散小波变换(DWT)部分数据之间的独立性适合并行化处理。NVIDIA最新推出的CUDA(计算统一设备架构)是非常适合大规模数据并行计算的软硬件开发平台。在通用计算图形处理器(General Purpose Graphic Process Unit,GPGPU)上使用CUDA技术实现DWT并行化加速,并针对GPGPU存储空间的特点进行优化。得出的实验结果表明,经过CUDA并行优化的方法能够有效地提高离散小波变换DWT的计算速度。In order to improve the compression speed of JPEG2000,the JPEG2000 compression standard is analysised and it concluded that the part data of the core algorithm that is DWT in JPEG2000 are independent from each other,so it is very suitable for parallel processing.CUDA（Compute Unified Device Architecture）is a latest software and hardware exploitation platform released by NVIDIA which is very suitable for large-scale data parallel computing.Using CUDA technology on general purpose graphic process unit（GPGPU）could speed up DWT algorithm parallelly and the program is optimized based on the characteristics of GPGPU storage space.The obtained experimental results show the DWT algorithm that is optimized by CUDA parallelly can improve the computing speed.

关 键 词：JPEG2000 离散小波变换 通用图形处理器 并行计算 CUDA 

分 类 号：TN911.73[电子电信—通信与信息系统]