By studying the traditional spectral reflectance reconstruction method, spectral reflectance and the relative spectral power distribution of a lighting source are sparsely decomposed, and the orthogonal property of th...By studying the traditional spectral reflectance reconstruction method, spectral reflectance and the relative spectral power distribution of a lighting source are sparsely decomposed, and the orthogonal property of the principal component orthogonal basis is used to eliminate basis; then spectral reflectance data are obtained by solving a sparse coefficient. After theoretical analysis, the spectral reflectance reconstruction based on sparse prior knowledge of the principal component orthogonal basis by a single-pixel detector is carried out by software simulation and experiment. It can reduce the complexity and cost of the system, and has certain significance for the improvement of multispectral image acquisition technology.展开更多
基金supported by the National Natural Science Foundation of China (Grant No.61405115)the Natural Science Foundation of Shanghai (Grant No.14ZR1428400)+1 种基金the Innovation Project of Shanghai Municipal Education Commission (Grant No.14YZ099)National Basic Research Program of China (973 Program) (Grant No.2015CB352004)
文摘By studying the traditional spectral reflectance reconstruction method, spectral reflectance and the relative spectral power distribution of a lighting source are sparsely decomposed, and the orthogonal property of the principal component orthogonal basis is used to eliminate basis; then spectral reflectance data are obtained by solving a sparse coefficient. After theoretical analysis, the spectral reflectance reconstruction based on sparse prior knowledge of the principal component orthogonal basis by a single-pixel detector is carried out by software simulation and experiment. It can reduce the complexity and cost of the system, and has certain significance for the improvement of multispectral image acquisition technology.
