Research on Parallelization of Scharr Operators Based on CUDA
Traditional edge detection operators use the method of seeking gradients row by row in order,which makes it difficult to meet the high computational density requirements of large image sizes or high computational speed.This paper designs the Scharr operator from the perspective of parallelization,optimizes the algorithm on two-dimensional data parallel computing using CUDA language,proposes a design idea for multithreaded block offset calculation,and adopts stream processing to reduce transmission overhead.Experiment results show that compared with the traditional Scharr operator,it exhibits efficient recognition speed in image recognition of sizes on 7 000×7 000,with an acceleration ratio increased by about 300 times,and has high application value.
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