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Image matching algorithm based on SIFT using color and exposure information 被引量:9
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作者 Yan Zhao Yuwei Zhai +1 位作者 Eric Dubois Shigang Wang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2016年第3期691-699,共9页
Image matching based on scale invariant feature transform(SIFT) is one of the most popular image matching algorithms, which exhibits high robustness and accuracy. Grayscale images rather than color images are genera... Image matching based on scale invariant feature transform(SIFT) is one of the most popular image matching algorithms, which exhibits high robustness and accuracy. Grayscale images rather than color images are generally used to get SIFT descriptors in order to reduce the complexity. The regions which have a similar grayscale level but different hues tend to produce wrong matching results in this case. Therefore, the loss of color information may result in decreasing of matching ratio. An image matching algorithm based on SIFT is proposed, which adds a color offset and an exposure offset when converting color images to grayscale images in order to enhance the matching ratio. Experimental results show that the proposed algorithm can effectively differentiate the regions with different colors but the similar grayscale level, and increase the matching ratio of image matching based on SIFT. Furthermore, it does not introduce much complexity than the traditional SIFT. 展开更多
关键词 scale invariant feature transform(SIFT) image matching color exposure
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