Adaptive Reconstruction of Harmonic Time Series Using Point-Jacobian Iteration MAP Estimation and Dynamic Compositing: Simulation Study
Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series contaminated by noises resulted from mechanical problems or sensing environmental condition. There is also a high likelihood that during the data acquisition periods the target site corresponding to any given pixel may be covered by fog or cloud, thereby resulting in bad or missing observation. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. A feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. The experimental results of this simulation study show the potentiality of the proposed system to reconstruct the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather. This study provides fundamental information on the elements of the proposed system for right usage in application.
- Townsend, J. R. G. and C. J. Tucker, 1984. Objective assessment of AVHRR data for land cover mapping, Int. J. Remote Sens., 5: 492-501.
- Melgani, F. and S. B. Serpico, 2003. A Markov random field approach to spatio-temporal contextual image classification, IEEE Trans. Geosci. Remote Sens., 41: 2478-2487.
- Fung, T., 1990. An assessment of TM imagery for land-cover change detection, IEEE Trans. Geosci. Remote Sensing, 28: 681-684.
- Horvath, N. C., T. I. Grey, and D. G. McCray, 1982. Advanced Very High Resolution Radiometer (AVHRR) data evaluation for use in monitoring vegetation, AgRISTAR Report EW-L@-040303, JSC-18243, NASA, Lyndon B. Johnson Space Center, Houston, TX., 1982.0-1365.
- Carlotto, M. J., 1985. Techniques for multispectral image classification, SPIE Digital Image Processing, 528: 174-191.
- Goldberg, M., G. Karem, and M. Alvo, 1983. A production rule-based expert system for interpreting multi-temporal LANDSAT imagery, CVPR'83 Proceedings.
- Khazenie, N. and M. M. Crawford, 1990. Spatialtemporal autocorrelated model for contextual classification, IEEE Trans. Geosci. Remote Sens., 28: 529-539.
- Jeon, B. and D. A. Landgrebe, 1999. Decision fusion approach for multitemporal classification, IEEE Trans. Geosci. Remote Sens., 37: 1227- 1233.
- Lee, S. and M. M. Crawford, 1991. Adaptive reconstruction system for spatially correlated multispectral multitemporal images, IEEE Trans. on Geosci. Remote Sens., 29: 494-503.
- Singh, A., 1989. Digital change detection techniques using remotely sensed data, Int. J. Remote Sensing, 10: 989-1003.
- Teng, W. L., 1990. AVHRR monitoring of US. Crops during the 1988 drought, Photogramm. Eng. Remote Sens., 56: 1143-1146.
- Cullen, C. G., 1972. Matrices and Linear Transformations. Reading, MA: Addison- Wesley.
- Tucker, C. J., N. B. Hoblen, J. H. Elgin, Jr, and J. E. Mcmurtey III, 1990. Relationship of spectral data to grain yield variation, Photogramm. Eng. Remote Sens., 46: 657-666.
- Tarpley, J. D., S. R. Schneider, and R. L. Money, 1984. Global vegetation indices from the NOAA-7 meteorological satellite, J. Climate Appl. Meteorol., 23: 491-494.
- Georgii, H. O., 1979. Canonical Gibbs Measure. Berlin, Germany: Springer-Verlag.
- Lee, S-H, 2007. Speckle Removal of SAR Imagery Using a Point-Jacobian Iteration MAP Estimation, Korean Journal of Remote Sensing, 23: 33-42.
- Townshend, J. R. G. and C. O. Justice, 1995. Spatial variability of imagesand the monitoring of changes in the normalized difference vegetation index, Int. J. Remote Sensing, 16(12): 2187-2195.
- Carlotto, M. J., 1997. Detection and analysis of change in remotely sensed imagery with application to wide area surveillance, IEEE Trans. Image Processing, 6: 189-202.
- Lee, S-H, 2002. Reconstruction and Change Monitoring of Image Series, Korean Journal of Remote Sensing, 18: 157-170 (Korean version).
이 논문을 인용한 문헌 (2)
- Lee, Sang-Hoon 2009. "Adaptive Reconstruction of NDVI Image Time Series for Monitoring Vegetation Changes" 대한원격탐사학회지 = Korean journal of remote sensing, 25(2): 95~105
- 2010. "" 대한원격탐사학회지 = Korean journal of remote sensing, 26(6): 721~730
- NDSL :
- 한국학술정보 : 저널
원문복사신청을 하시면, 일부 해외 인쇄학술지의 경우 외국학술지지원센터(FRIC)에서
무료 원문복사 서비스를 제공합니다.
NDSL에서는 해당 원문을 복사서비스하고 있습니다. 위의 원문복사신청 또는 장바구니 담기를 통하여 원문복사서비스 이용이 가능합니다.
- 이 논문과 함께 출판된 논문 + 더보기