Fast image registration via joint gradient maximization: application to multi-modal data

Xue Mei; Fatih Porikli

doi:10.1117/12.690077

5 October 2006 Fast image registration via joint gradient maximization: application to multimodal data

Xue Mei, Fatih Porikli

Proceedings Volume 6395, Electro-Optical and Infrared Systems: Technology and Applications III; 63950P (2006) https://doi.org/10.1117/12.690077
Event: Optics/Photonics in Security and Defence, 2006, Stockholm, Sweden

Abstract

We present a computationally inexpensive method for multi-modal image registration. Our approach employs a joint gradient similarity function that is applied only to a set high spatial gradient pixels. We obtain motion parameters by maximizing the similarity function by gradient ascent method, which secures a fast convergence. We apply our technique to the task of affine model based registration of 2D images which undergo large rigid motion, and show promising results.

Citation Download Citation

Xue Mei and Fatih Porikli "Fast image registration via joint gradient maximization: application to multimodal data", Proc. SPIE 6395, Electro-Optical and Infrared Systems: Technology and Applications III, 63950P (5 October 2006); https://doi.org/10.1117/12.690077

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