Based on linear spectral mixture model (LSMM) Unmixing remote sensing image

There are mixed pixels in remote sensing images ordinarily, this is a difficulty of the pixel classification (ie, unmixing) in remote sensing image processing. Linear spectral separation, estimating the value end of Genpo degree, for spatial modeling, through the non-constrained mixed pixel decomposition, with cotton, corn, tomatoes and soil four endmembers to decompose mixed pixels, Got four endmember abundance images and the RMS error image, the planting area of cotton and cotton-growing area of the measurement in the decomposition of mixed pixel block, and obtained unmixing accuracy. Experimental results show that: a simple linear mixed model modeling, and computation is greatly reduced, high precision, strong adaptability.