A mapping method of image mosaic algorithm on embedded reconfigurable processor

Abstract

A mapping method of image mosaic algorithm based on Reconfigurable Processing Element Array (RPEA) is proposed. This method can effectively improve the utilization rate of parallel resources. In the image mosaic algorithm, Harris corner detection is used to extract the feature points. Normalized Cross Correlation (NCC) algorithm is used to match these feature points and Random sample consensus (RANSAC) algorithm is used to eliminate the mismatching. Critical parts of the algorithms described in C language are found out, which are dynamically mapped onto the RPEA to run concurrently. The execution time on RPEA is reported to compare with execution time on general single-core processor. This paper focuses on the mapping methods based on loop unrolling and software pipeline loop and proposes an optimized method. The test results show that the speedups of mapping the mosaic algorithm on the reconfigurable processor with the proposed method versus using Intel Atom 230 reach more than 2.