Mixed pixel classification with the randomized Hough transform

Proceedings - International Conference on Pattern Recognition

Volumn 2, Issue , 1996, Pages 576-580

  Kalviainen, H ^a,b   Bosdogianni, P ^a   Petrou, M ^a   Kittler, J ^a  

^a UNIVERSITY OF SURREY   (United Kingdom)

^b LAPPEENRANTA UNIVERSITY OF TECHNOLOGY   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

SOFTWARE ENGINEERING;

CLASSICAL LEAST SQUARES; LARGE DATASETS; MIXED PIXEL; MIXED PIXEL CLASSIFICATION; RANDOMIZED HOUGH TRANSFORM;

PATTERN RECOGNITION;

EID: 84898818817     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.1996.546889     Document Type: Conference Paper

References (8)

1. J. Adams, M. Smith, and P. Johnson. Spectral mixture modeling: A new analysis of rock and soil types at the viking lander 1 site. Journal of geophysical research, 91(B8):8098-8112, 1986.
2. P. Bosdogianni, M. Petrou, and J.Kittler. Robust mixed pixel classification in remote sensing. In VIII ISPRS-Congress, Vienna, Austria, July 1996.
3. P. Bosdogianni, M. Petrou, and J. Kittler. Mixed pixel classification in remote sensing. In Image and Signal Processing for Remote Sensing, volume 2315 of EUROPTO, pages 494-505. SPIE, 1994.
4. P. Bosdogianni, M. Petrou, and J. Kittler. Robust mixed pixel classification using the hypothesis testing hough transform'. In IGARSS, Lincoln, Nebraska, USA, May 1996.
5. D. Foody and D. Cox. Sub-pixel land cover composition estimation using a linear mixture model and fuzzy membership functions. Int. Journal of Remote Sensin, 15, 1993.
6. P. Gong, J. Miller, and M. Spanner. Forest canopy closure from classification and spectral unmixing to scene components-multisensor evaluation of an open canopy. IEEE Trans. Geosci. Remote Sensing, 32(5): 1067-1079, 1994.
7. H. Kalviainen, P. Hirvonen, L. Xu, and E. Oja. Probabilistic and non-probabilistic hough transforms: Overview and comparisons. Image and Vision Computing, 13(4):239-252, 1995.
8. L. Xu, E. Oja, and P. Kultancn. A new curve detection method: Randomized hough transform (rht). Pattern Recognition Letters, ll(5):331-338, 1990.