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Efficient and Robust Direct Image Registration Based on Joint Geometric and Photometric Lie Algebra
Li CX(李晨曦)1,2,3; Shi ZL(史泽林)1,2,3; Liu YP(刘云鹏)1,2,3; Liu TC(刘天赐)1,2,3; Xu LY(许凌云)1,2,3
Department光电信息技术研究室
Source PublicationIEEE TRANSACTIONS ON IMAGE PROCESSING
ISSN1057-7149
2018
Volume27Issue:12Pages:6010-6024
Indexed BySCI ; EI
EI Accession number20183405732119
WOS IDWOS:000444019600022
Contribution Rank1
Funding OrganizationKey Laboratory Foundation of Chinese Academy of Sciences
KeywordImage Registration Photometric Variations Photometric Transformation Lie Group Lie Algebra
Abstract

This paper considers the joint geometric and photometric image registration problem. The inverse compositional (IC) algorithm and the efficient second-order minimization (ESM) algorithm are two typical efficient methods applied to the geometric registration problem. Their efficiency stems from the utilization of the group structure of geometric transformations. To allow for photometric variations, the dual IC algorithm (DIC) proposed by Bartoli performs joint geometric and photometric image registration by extending the IC algorithm. The group structures of both geometric and photometric transformations are exploited. Despite the robustness to large photometric variations, DIC is vulnerable to large geometric deformations. The ESM algorithm is extended by Silveira et al. to address photometric variations. In their approach, the photometric transformations are modeled in Euclidean space. Their approach is robust to relatively large geometric and photometric transformations; however, it is not efficient for large photometric variations. We propose a new efficient and robust image registration method by exploiting the non-Euclidean Lie group structure of joint geometric and photometric transformations for both grayscale and color images. The image registration is formulated as a nonlinear least squares problem. In our method, the geometric and photometric transformations are jointly parameterized by their corresponding Lie algebras. Based on this parameterization approach, the second-order approximation strategy of ESM is employed to optimize the joint geometric and photometric parameters. The error function in the nonlinear least squares problem is approximated by a second-order Taylor expansion with respect to joint geometric and photometric parameters without computing the Hessian matrix. For further efficiency, independent convergence criteria for geometric and photometric parameters are used in the iterative optimization process. The superiority of our proposed method over the previous methods, in terms of efficiency, accuracy, and robustness, is demonstrated through extensive experiments on synthetic and real data.

Language英语
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS KeywordVisual Tracking ; Lucas-kanade ; Models ; Illumination ; Descriptors
WOS Research AreaComputer Science ; Engineering
Funding ProjectKey Laboratory Foundation of Chinese Academy of Sciences[Y0A4106401]
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/22425
Collection光电信息技术研究室
Corresponding AuthorLi CX(李晨曦)
Affiliation1.University of Chinese Academy of Sciences, Beijing 100049, China
2.Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences
3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, P.R.China.
Recommended Citation
GB/T 7714
Li CX,Shi ZL,Liu YP,et al. Efficient and Robust Direct Image Registration Based on Joint Geometric and Photometric Lie Algebra[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2018,27(12):6010-6024.
APA Li CX,Shi ZL,Liu YP,Liu TC,&Xu LY.(2018).Efficient and Robust Direct Image Registration Based on Joint Geometric and Photometric Lie Algebra.IEEE TRANSACTIONS ON IMAGE PROCESSING,27(12),6010-6024.
MLA Li CX,et al."Efficient and Robust Direct Image Registration Based on Joint Geometric and Photometric Lie Algebra".IEEE TRANSACTIONS ON IMAGE PROCESSING 27.12(2018):6010-6024.
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