A normalized surf for multispectral image matching and band co-registration

J. P. Jhan, J. Y. Rau

研究成果: Conference article

摘要

Due to the raw images of multi-lens multispectral (MS) camera has significant misregistration errors, performing image registration for band co-registration is necessary. Image matching is an essential step for image registration, which obtains conjugate features on the overlapped areas, and use them to estimate the coefficients of a transformation model for correcting the geometrical errors. However, due to the none-linear intensity of spectral response, performing feature-based image matching (such as SURF) can only obtain only a few conjugate features on cross-band MS images. Different to SURF that extracts local extremum in a multi-scale space and utilizes a threshold to determine a feature, we proposed a normalized SURF (N-SURF) that extracts features on single scale, calculates the cumulative distribution function (CDF) of features, and obtains consistent features from the CDF. In this study, two datasets acquired from Tetracam MiniMCA-12 and Micasense RedEdge Altum are used for evaluating the matching performance of N-SURF. Results show that N-SURF can extract approximately 2–3 times number of features, match more points, and have more efficient than original SURF. On the other hand, with the successful of MS image matching, we can therefor use the conjugates to compute the coefficients of a geometric transformation model. In this study, three transformation models are used to compare the difference on MS band co-registration, i.e. affine, projective, and extended projective. Results show that extended projective model is better than the others as it can compensate the difference of lens distortion and viewpoint, and has co-registration accuracy of 0.3–0.6 pixels.

原文English
頁(從 - 到)393-399
頁數7
期刊International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
42
發行號2/W13
DOIs
出版狀態Published - 2019 六月 4
事件4th ISPRS Geospatial Week 2019 - Enschede, Netherlands
持續時間: 2019 六月 102019 六月 14

    指紋

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Geography, Planning and Development

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