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Image processing grosses much more time to perform the convolution in image filtering on CPU, since the computation demand of image filtering is enormous.
Finally, the results show how the image processing task that required tens of hours to complete can be processed by using only a fraction of the originally required computing time.
Such levels of performance make the processing capacities of current image processing technology look positively feeble.
Parallel architectures offer a promising method for speeding up these image processing operations.
Open accessProceedings ArticleDOI
Nitin Singhal, In Kyu Park, Sung-Dae Cho 
03 Dec 2010
47 Citations
By using the image processing toolkit, we show that a range of image processing algorithms map readily to handheld GPU.
The paper presents an efficient and flexible framework for extensive image processing tasks.
Proceedings ArticleDOI
01 Dec 2007
9 Citations
Moreover, they exhibit excellent execution times as compared to recent dedicated image processing architectures.

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