GPU-Accelerated Discrete Wavelet Transform for Images
Yu Min Chen, Fei Zeng, Jing Yang Wu, Qiao Wan, Zhi Jun Su · Advanced materials research · 2013
Discrete Wavelet Transform (DWT) has been brought into wide use in image processing, but it cant fit the demand of the hugeimage data because the time of computing is vast. The GPU is an attractive platform for a broad fieldof applications,which remains asignificanthigharithmetic processingcapability. Therefore itcan beusedasa powerful accelerator without extra cost.CUDA(computeunifieddevicearchitecture) providesahardwareandsoftwareenvironment touse the GPU to accelerate the DWT for images. In this paper, we use the NVIDIA GeForce GT 650M that complies with the CUDA to improvethe execution time of theDiscrete Wavelet Transformfor images. TheresultofexperimentsindicatesthattheCUDAtechnology hastheadvantagesof parallel processingandtheefficiencyofimagetransform isimprovedgreatly. Whats more, it performs better on the larger size image (the max speedup is 15.9).