Volume 32 Issue 1
Jan.  2012
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LU Jinbo, HE Bin. Automatic Mosaic Method of Large Field View and Multi-Channel Remote Sensing Images of TDICCD Cameras[J]. Journal of Space Science, 2012, 32(1): 154-160. doi: 10.11728/cjss2012.01.154
Citation: LU Jinbo, HE Bin. Automatic Mosaic Method of Large Field View and Multi-Channel Remote Sensing Images of TDICCD Cameras[J]. Journal of Space Science, 2012, 32(1): 154-160. doi: 10.11728/cjss2012.01.154

Automatic Mosaic Method of Large Field View and Multi-Channel Remote Sensing Images of TDICCD Cameras

doi: 10.11728/cjss2012.01.154
  • Received Date: 2010-08-06
  • Rev Recd Date: 2011-08-29
  • Publish Date: 2012-01-15
  • In terms of mosaic of TDICCD large field view and multi-channel remote sensing images, noise immunity and robustness of the previous classical method is not high, which is difficult to achieve high accuracy and fast image mosaic because of imaging resonance, flutter and other factors in the imaging platforms. For that reason, this paper proposes a more appropriate method, namely the spatial cross-correlation self-tuning sub-pixel registration method. Firstly, because of the characteristics of overlapping pixels between TDICCD multi-channel images, the method uses the cross correlation of variable search window as the evaluation function. Secondly, the local detection method is employed to monitor change of parameter to figure out the best parameters of each part of images. Thirdly, the matching error points are controlled by interference elimination method, so that parameters are more credible. Finally, sub-pixel locating algorithm is proposed to reduce error of image registration. The results of practical remote sensing image mosaic indicate that accuracy of the algorithm excesses 0.1pixel, while rapidity, stability, noise immunity and robustness are higher than other methods and image mosaic obtains expected results.

     

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