Optical and SAR image registration based on improved nonsubsampled wavelet transform for sea islands

SHI Wei; SU Fenzhen; WANG Ruirui; LU Yongduo

doi:10.1007/s13131-014-0474-x

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Article Navigation > Acta Oceanologica Sinica > 2014 > 33(5): 86-95

SHI Wei, SU Fenzhen, WANG Ruirui, LU Yongduo. Optical and SAR image registration based on improved nonsubsampled wavelet transform for sea islands[J]. Acta Oceanologica Sinica, 2014, 33(5): 86-95. doi: 10.1007/s13131-014-0474-x

Citation:

SHI Wei, SU Fenzhen, WANG Ruirui, LU Yongduo. Optical and SAR image registration based on improved nonsubsampled wavelet transform for sea islands[J]. Acta Oceanologica Sinica, 2014, 33(5): 86-95. doi: 10.1007/s13131-014-0474-x

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Optical and SAR image registration based on improved nonsubsampled wavelet transform for sea islands

doi: 10.1007/s13131-014-0474-x

1.
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210093, China
2.
Beijing Forestry University, Beijing 100083, China
3.
National Marine Environmental Forecasting Center, State Oceanic Administration, Beijing 100081, China

Received Date: 2012-12-05
Rev Recd Date: 2013-09-22

Abstract

Abstract

Homologous feature point extraction is a key problem in the optical and synthetic aperture radar (SAR) image registration for islands. A new feature point extraction method using a threshold shrink operator and non-subsampled wavelet transform (TSO-NSWT) for optical and SAR image registration was proposed. Moreover, the matching for this proposed feature was different from the traditional feature matching strategies and was performed using a similarity measure computed from neighborhood circles in low-frequency bands. Then, a number of reliably matched couples with even distributions were obtained, which assured the accuracy of the registration. Application of the proposed algorithm to SPOT-5 (multi-spectral) and YG-1 (SAR) images showed that a large number of accurately matched couples could be identified. Additionally, both of the root mean square error (RMSE) patterns of the registration parameters computed based on the TSO-NSWT algorithm and traditional NSWT algorithm were analyzed and compared, which further demonstrated the effectiveness of the proposed algorithm. The algorithm can supply the crucial step for island image registration and island recognition.
- image registration

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References(18)

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