Geometric Abundance Estimation Using Variable Endmembers for Hyperspectral Imagery
نویسندگان
چکیده
منابع مشابه
Geometric Abundance Estimation Using Variable Endmembers for Hyperspectral Imagery
Abundance estimation is an important step of quantitative analysis of hyperspectral remote sensing data. Due to physical interpretation, sum-to-one and non-negativity constraints are generally imposed on the abundances of materials. This paper presents a geometric approach to fully constrained linear spectral unmixing using variable endmember sets for the pixels. First, an improved method for s...
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ABSTRACT The linear mixing model (LMM) is a well-known and useful method for decomposing spectra in a hyperspectral image into the sum of their constituents, or endmembers. Mathematically, if the spectra are represented as n-dimensional vectors, then the LMM implies that the set of endmembers defines a basis or coordinate system for the set of spectra. Because the endmembers themselves are gene...
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ژورنال
عنوان ژورنال: International Journal of Hybrid Information Technology
سال: 2014
ISSN: 1738-9968
DOI: 10.14257/ijhit.2014.7.3.14