:: Volume 7, Issue 1 (5-2019) ::
jgit 2019, 7(1): 193-210 Back to browse issues page
Fast Least Square Matching
Amin Sedaghat *, Nazila Mohammadi
University of Tabriz
Abstract:   (1236 Views)
Least square matching (LSM) is one of the most accurate image matching methods in photogrammetry and remote sensing. The main disadvantage of the LSM is its high computational complexity due to large size of observation equations. To address this problem, in this paper a novel method, called fast least square matching (FLSM) is being presented. The main idea of the proposed FLSM is decreasing the size of the observation equations to improve the efficiency of the matching process. For this purpose, the pixels in the matching window are ordered using a special robustness measure. Then, a specific percent of the pixels with the highest robustness is selected for matching process. The phase congruency and entropy measures are used to compute the proposed robustness measure. The proposed FLSM method was successfully applied to match various synthetic and real image pairs, and the results demonstrate its capability to increase matching efficiency. The matching results show that the proposed FLSM method is three times faster than standard LSM method.
Keywords: Image matching, Least square, Robustness, Efficiency.
Full-Text [PDF 2151 kb]   (489 Downloads)    
Type of Study: Research | Subject: Aerial Photogrammetry
Received: 2018/01/30 | Accepted: 2018/09/1 | Published: 2019/06/21



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Volume 7, Issue 1 (5-2019) Back to browse issues page