Pixel Discontinuity Repairing for Push-Broom Orthorectified Images

Jyun-Yi Lai, Ming-Fu Chen, Han-Chao Chang

Instrument Technology Research Center, National Applied Research Laboratories, Hsinchu, Chinese Taipei..

DOI: 10.4236/jsea.2013.64A004                

Abstract

Pixel discontinuity in orthoimages occurs frequently due to altitude variations in the pitch and heading of an airplane, and low performance of real-time analyzing software. This study proposes a scheme to resolve pixel discontinuity. The proposed scheme includes the following steps: 1) capture images by a self-made hyperspectral imager; 2) determine the pixel locations of orthoimages using a top-down approach; 3) repair discontinuities by the Nearest Neighbor (NN) or Bilinear Interpolation (BL) approaches; and, 4) perform a dynamic range adjustment on the orthoimages, according to the maximum pixel value of the raw images and orthoimages. After applying the proposed scheme, this study found that pixel discontinuity was eliminated by both approaches, and that the software dependability and image quality were improved substantially. In addition, the computational efficiency of the NN approach was roughly two minutes faster than that of the BL due to its simpler computation. However, BL produces smoother image edges for landscapes.

Keywords

Pixel Discontinuity; Real-Time Analyzing Software; Top-Down Approach; Orthorectification

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	W. Mayr and C. Heipke, “A Contribution to Digital Orthophoto Generation,” International Archives of Photogrammetry and Remote Sensing, Vol. 27, No. B11, 1988, pp. 430-439.
[2]	L. C. Chen and L. H. Lee, “Rigorous Generation of Digital Orthophotos from SPOT Images,” Photogrammetric Engineering & Remote Sensing, Vol. 59, No. 5, 1993, pp. 655-661.
[3]	J. Allebach and P. W. Wong, “Edge-Directed Interpolation,” Proceedings of International Conference on Image Processing, Vol. 3, 1996, pp. 707-710.
[4]	C. F. Lee and Y. L. Huang, “An Efficient Image Interpolation Increasing Payload in Reversible Data Hiding,” Expert Systems with Applications, Vol. 39, No. 15, 2012, pp. 6712-6719. doi:10.1016/j.eswa.2011.12.019
[5]	Q. Tang, G. Y. Zhang, G. R. Liu, Z. H. Zhong and Z. C. He, “An Efficient Adaptive Analysis Procedure Using the Edgebased Smoothed Point Interpolation Method (ESPIM) for 2D and 3D Problems,” Engineering Analysis with Boundary Elements, Vol. 36, No. 9, 2012, pp. 1424-1443. doi:10.1016/j.enganabound.2012.03.007
[6]	R. S. V. Teegavarapu, T. Meskele and C. S. Pathak, “GeoSpatial Grid-Based Transformations of Precipitation Estimates Using Spatial Interpolation Methods,” Computers & Geosciences, Vol. 40, 2012, pp. 28-39. doi:10.1016/j.cageo.2011.07.004
[7]	R. J. Aspinall, W. A. Marcus and J. W. Boardman, “Considerations in Collecting, Processing, and Analyzing High Spatial Resolution Hyperspectral Data for Environmental Investigations,” Geograph System, Vol. 4, No. 1, 2002, pp. 15-29.
[8]	E. Puckrin, C. S. Turcotte, P. Lahaie, D. Dubé, V. Farley, P. Lagueux, F. Marcotte and M. Chamberland, “Airborne Infrared-Hyperspectral Mapping for Detection of Gaseous and Solid Targets,” Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XI, Vol. 7665, 2010, 10 Pages.
[9]	J. Liu, Y. S. Zhang, D. H. Wang and W. M. Xu, “Geometric Rectification of Airborne Linear Array Pushbroom Imagery Supported by INS/DGPS System,” Journal of Remote Sensing, Vol. 10, No. 1, 2006, pp. 21-26.
[10]	V. A. Grishin, “Accuracy of Measuring Camera Position by Marker Observation,” Journal of Software Engineering and Applications, Vol. 3, No. 10, 2010, pp. 906-913. doi:10.4236/jsea.2010.310107
[11]	M. F. Chen, J. Y. Lai, L. J. Lee and T. M. Huang, “Defective CCDs Detection and Image Restoration Based on Inter-Band Radiance Interpolation for Hyperspectral Imager,” Proceeding of SPIE Asia-Pacific REMOTE Sensing, Vol. 7857, 2010, Article ID: 78570W, 12 Pages.