Mixed pixel decomposition method for remote sensing images
A hybrid pixel decomposition and remote sensing image technology, applied in the field of remote sensing image processing, can solve problems such as the inability to obtain an optimal solution, and achieve the effect of overcoming the tendency to fall into local minima and effectively mixing pixel decomposition.
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Embodiment 1
[0158] 1. Simulation data
[0159] Artificially generated simulation data are used to test the performance of the algorithm. The ASSNMF proposed by the present invention is compared with the following unmixing algorithms for hyperspectral images: VCA [9], PSNMFSC [10] with spectrum and abundance smoothness and abundance sparsity constraints, and minimum volume constraints The MVCNMF [11]. Among them, VCA can only get the spectral matrix, and other methods can directly solve the spectrum and abundance from the data. For VCA, the present invention uses the FCLS algorithm [8] on the basis of the spectrum it solves to obtain the corresponding abundance, and this method is recorded as VCA-FCLS.
[0160] The present invention uses two indexes of spectral angular distance (Spectral Angel Distance, SAD) and root mean square error (Root Mean Square Error, RMSE) to measure the pros and cons of the unmixing result. These two indicators are used to measure the approximation of the spec...
Embodiment 2
[0174] Embodiment 2 Actual data experiment
[0175] Three actual hyperspectral remote sensing image datasets are used to test the performance of the proposed algorithm.
[0176] The first dataset is the Indiana data captured by the Airborne Visible / Infrared Imaging Spectrometer (AVIRIS). It was imaged in June 1992. The imaging area is the Pine remote sensing test site in Indiana, USA. The data has 220 bands, the wavelength range is from 0.4:2.5μm, the spectral resolution is 10nm, and the spatial resolution is 17m. The image size used in the experiments is 145×145. This data has been widely used in the research and comparison of hybrid pixel decomposition algorithms for remote sensing images. Purdue University has given a field survey report on the area [12]. This area is a piece of farmland located about 10km northwest of West Lafayette, IN, Indiana. The area is mainly covered by various crops (about two-thirds, including corn, wheat, soybeans, haystacks) and natural veget...
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