earticle

영어

An image stitching algorithm based on the robustness of principal component analysis (RPCA) is proposed in an effort to suppress the influence of noise in the image stitching quality. This algorithm represents high dimensional feature data by utilizing a lower dimensional linear subspace, and converts the image stitching problem into a principal component matrix matching problem. Through the use of a low rank matrix, the extraction of salient image characteristics is recovered and the noise interference is reduced during the enhancement process. Together, with the advantages of the RPCA algorithm, the algorithm improves the PSNR of the image while maintaining its strong matching ability. Experimental results show that the proposed scheme is able to significantly inhibit the noise and improve the stitching quality in comparison to the other existing stitching methods.