基于GPGPU的JPEG2000图像压缩方法

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DWT的计算速度。

JPEG2000 image compression method based on GPGPU

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 .