Multispectral and hyperspectral image processing based on the waveform characteristics of spectral remote sensing classification method of large area

Qingqing Peng; Liao Yang; Jinxiang Shen

doi:10.1117/12.901586

8 December 2011 Multispectral and hyperspectral image processing based on the waveform characteristics of spectral remote sensing classification method of large area

Qingqing Peng, Liao Yang, Jinxiang Shen

Author Affiliations +

Proceedings Volume 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis; 80020Z (2011) https://doi.org/10.1117/12.901586
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

Determination of land cover spatial distribution and change scientifically and accurately have a great significance for monitoring the regional ecological environment and the impact of human activities. This paper proposed a method basing on the waveform characteristics of spectral for mapping large area using TM data simply, quickly and accurately. In the experiments, we segment the image to object and order the object value of the TM5 1~7 except the thermal infrared band and each order result given the only value. In the next, using manual methods assigned the order to get the typical surface feature such as water, soil, vegetation. Classification using spectral waveform characteristics can effectively avoid the TM image classification error, due to spectral differences by accessing time and spatial, spectrum differences on same object and spectral mixing .This method can map the large area of typical surface is simply, fast and accurate, and support on theoretical basis.

Citation Download Citation

Qingqing Peng, Liao Yang, and Jinxiang Shen "Multispectral and hyperspectral image processing based on the waveform characteristics of spectral remote sensing classification method of large area", Proc. SPIE 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, 80020Z (8 December 2011); https://doi.org/10.1117/12.901586

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