Calibration of a pushbroom hyperspectral imaging system for agricultural inspection

Transactions of the American Society of Agricultural Engineers

Volumn 46, Issue 2, 2003, Pages 513-521

  Lawrence, Kurt C ^a   Park, B ^a   Windham, W R ^a   Mao, C ^b  

^a RUSSELL RESEARCH CENTER   (United States)

^b STENNIS SPACE CENTER   (United States)

Author keywords

Hyperspectral imaging system; Imaging calibration; Imaging spectrometry; Percent reflectance; Spectrometer; Spectroscopy

Indexed keywords

AGRICULTURE; DETECTORS; ERROR ANALYSIS;

PUSHBROOM HYPERSPECTRAL IMAGING SYSTEMS;

IMAGING SYSTEMS;

IMAGING METHOD;

EID: 0038269680     PISSN: 00012351     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (27)

1. Badhwar, G. D., J. G. Cames, and W. W. Austin. 1982. Use of Landsat-derived temporal profiles for corn-soybean feature extraction and classification. Remote Sensing of Environment 12(1): 57-59.
2. Chao, K., P. M. Mehl, and Y. R. Chen. 2000a. Use of hyper- and multi-spectral imaging for detection of chicken skin tumors. ASAE Paper No. 003084. St. Joseph, Mich.: ASAE.
3. Chao, K., B. Park, Y. R. Chen, W. R. Hruschka, and F. W. Wheaton. 2000b. Design of a dual system for poultry carcasses inspection. Applied Eng. in Agric. 16(5): 581-587.
4. Chao, K., Y.-R. Chen, W. R. Hruschka, and B. Park. 2001. Chicken heart disease characterization by multi-spectral imaging. Applied Eng. in Agric. 17(1): 99-106.
5. Chen, Y. R., and D. R. Massie. 1993. Visible/near infrared reflectance and interactance spectroscopy for detection of abnormal poultry carcasses. Trans. ASAE 36(3): 863-889.
6. Chen, Y. R., R. W. Huffman, B. Park, and M. Nguyen 1996. Transportable spectrophotometer system for on-line classification of poultry carcasses. Applied Spectroscopy 50: 910-916.
7. Chrien, T. G. 1999. Calibration and validation of imaging spectrometry data. Denver, Colo.: SPIE Short Course.
8. Fisher, J., M. Baumback, J. Bowles, J. Grossmann, and J. Antoniades. 1998. Comparison of low-cost hyperspectral sensors. Proc. SPIE 3438: 23-30.
9. Gupta, N., and R. Dahmani. 1999. Multispectral and hyperspectral imaging with AOTF for object recognition. In 27th AIPR Workshop: Advances in Computer-Assisted Recognition. R. J. Mericsko, ed. Proc. SPIE 3584: 128-135.
10. Haralick, R. M., C. A. Hlavka, R. Yokoyama, and S. M. Carlyle. 1980. Spectral-temporal classification using vegetation phenology. IEEE Trans. Geoscience and Remote Sensing GE-18: 167-174.
11. Hart, C. L., W. J. Slough, and J. B. Rafert. 1998. A review of hyperspectral imagers and comparison with respect to real time processing on space and aircraft platforms. Proc. SPIE 3389: 139-149.
12. Heitschmidt, J., M. Lanoue, C. Mao, and G. May. 1998. Hyperspectral analysis of fecal contamination: a case study of poultry. Proc. SPIE 3544: 134-137.
13. Lu, R., and Y. R. Chen. 1998. Hyperspectral imaging for safety inspection of food and agricultural products. Proc. SPIE 3544: 121-133.
14. Lu, R., Y. R. Chen, B. Park, and K. H. Choi. 1999. Hyperspectral imaging for detecting bruises in apples. ASAE Paper No. 993120. St. Joseph, Mich.: ASAE.
15. Mao, C. 2000. Focal plane scanner with reciprocating spatial window. U.S. Patent No. 6,166,373.
16. Oriel. 1996. Typical spectra of Oriel instruments spectral calibration lamps. Stratford, Conn.: Oriel Instruments.
17. Park, B., and Y. R. Chen. 1996. Multispectral image co-occurrence matrix analysis for poultry carcass inspection. Trans. ASAE 39(4): 1485-1491.
18. Park, B., Y. R. Chen, M. Nguyen, and H. Hwang. 1996. Characterizing multispectral images of tumorous, bruised, skin-torn, and wholesome poultry carcasses. Trans. ASAE 39(5): 1933-1941.
19. Schowengerdt, R. A. 1997. Remote Sensing: Models and Methods for Image Processing. San Diego, Cal.: Academic Press.
20. Spectral Imaging. 1997. ImSpector Imaging Spectrograph User Manual. Ver. 1.7. Oulu, Finland: Spectral Imaging, Ltd.
21. Suhre, D. R., L. H. Taylor, N. B. Singh, and W. R. Rosch. 1999. Comparison of acousto-optic tunable filters and acousto-optic dispersive filters for hyperspectral imaging. In 27th AIPR Workshop: Advances in Computer-Assisted Recognition. R. J. Mericsko, ed. Proc. SPIE 3584: 142-147.
22. Vane, G. 1987. Airborne visible/infrared imaging spectrometer (AVIRIS). JPL Publication 87-38. Pasadena, Cal.: Jet Propulsion Laboratory.
23. Willoughby, C. T., M. A. Folkman, and M. A. Figueroa. 1996. Application of hyperspectral imaging spectrometer systems to industrial inspection. Proc. SPIE 2599: 264-272.
24. Wolberg, G. 1990. Digital Image Warping. Los Alamitos, Cal.: IEEE Computer Society Press.
25. Wolfe, W. L. 1997. Introduction to Imaging Spectrometers. Bellingham, Wash.: SPIE Optical Engineering Press.
26. USDA. 1994. Enhanced poultry inspection. Proposed Rule. Fed. Reg. 59: 35659.
27. _. 1996. Pathogen reduction; hazard analysis and critical control point (HACCP) systems. Final Rule. Fed. Reg. 61: 28805-38855.