2 March 2016 An improved SIFT algorithm based on KFDA in image registration
Author Affiliations +
Proceedings Volume 9901, 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015); 99010G (2016) https://doi.org/10.1117/12.2234856
Event: 2015 ISPRS International Conference on Computer Vision in Remote Sensing, 2015, Xiamen, China
Abstract
As a kind of stable feature matching algorithm, SIFT has been widely used in many fields. In order to further improve the robustness of the SIFT algorithm, an improved SIFT algorithm with Kernel Discriminant Analysis (KFDA-SIFT) is presented for image registration. The algorithm uses KFDA to SIFT descriptors for feature extraction matrix, and uses the new descriptors to conduct the feature matching, finally chooses RANSAC to deal with the matches for further purification. The experiments show that the presented algorithm is robust to image changes in scale, illumination, perspective, expression and tiny pose with higher matching accuracy.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peng Chen, Lijuan Yang, Jinfeng Huo, "An improved SIFT algorithm based on KFDA in image registration", Proc. SPIE 9901, 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015), 99010G (2 March 2016); doi: 10.1117/12.2234856; https://doi.org/10.1117/12.2234856
PROCEEDINGS
10 PAGES


SHARE
Back to Top