A simple and effective approach is proposed to minimize the effect of unmodulated light and uneven intensity caused by the pixelated structure of the spatial light modulator in a holographic display. A more uniform im...A simple and effective approach is proposed to minimize the effect of unmodulated light and uneven intensity caused by the pixelated structure of the spatial light modulator in a holographic display. A more uniform image is produced by purposely shifting the holographic images of multiple reconstructed lights with different incident angles from the zero-diffraction-order and overlapping those selected different orders. The simulation and optical experimental results show that the influence of the zero-diffraction-order can be reduced, while keeping the good uniformity of the target images by this new approach.展开更多
Endmember extraction is a key step in the hyperspectral image analysis process. The kernel new simplex growing algorithm （KNSGA）, recently developed as a nonlinear alternative to the simplex growing algorithm （SGA...Endmember extraction is a key step in the hyperspectral image analysis process. The kernel new simplex growing algorithm （KNSGA）, recently developed as a nonlinear alternative to the simplex growing algorithm （SGA）, has proven a promising endmember extraction technique. However, KNSGA still suffers from two issues limiting its application. First, its random initialization leads to inconsistency in final results; second, excessive computation is caused by the iterations of a simplex volume calculation. To solve the first issue, the spatial pixel purity index （SPPI） method is used in this study to extract the first endrnember, eliminating the initialization dependence. A novel approach tackles the second issue by initially using a modified Cholesky fac- torization to decompose the volume matrix into triangular matrices, in order to avoid directly computing the determinant tauto- logically in the simplex volume formula. Theoretical analysis and experiments on both simulated and real spectral data demonstrate that the proposed algorithm significantly reduces computational complexity, and runs faster than the original algorithm.展开更多
基金supported by the UK Engineering and Physical Sciences Research Council(EPSRC) for the support through the EPSRC Centre for Innovative Manufacturing in Ultra Precision(EP/I033491/1)
文摘A simple and effective approach is proposed to minimize the effect of unmodulated light and uneven intensity caused by the pixelated structure of the spatial light modulator in a holographic display. A more uniform image is produced by purposely shifting the holographic images of multiple reconstructed lights with different incident angles from the zero-diffraction-order and overlapping those selected different orders. The simulation and optical experimental results show that the influence of the zero-diffraction-order can be reduced, while keeping the good uniformity of the target images by this new approach.
基金Project supported by the Zhejiang Provincial Natural Science Foundation of China(Nos.LY13F020044 and LZ14F030004)the National Natural Science Foundation of China(No.61571170)
文摘Endmember extraction is a key step in the hyperspectral image analysis process. The kernel new simplex growing algorithm （KNSGA）, recently developed as a nonlinear alternative to the simplex growing algorithm （SGA）, has proven a promising endmember extraction technique. However, KNSGA still suffers from two issues limiting its application. First, its random initialization leads to inconsistency in final results; second, excessive computation is caused by the iterations of a simplex volume calculation. To solve the first issue, the spatial pixel purity index （SPPI） method is used in this study to extract the first endrnember, eliminating the initialization dependence. A novel approach tackles the second issue by initially using a modified Cholesky fac- torization to decompose the volume matrix into triangular matrices, in order to avoid directly computing the determinant tauto- logically in the simplex volume formula. Theoretical analysis and experiments on both simulated and real spectral data demonstrate that the proposed algorithm significantly reduces computational complexity, and runs faster than the original algorithm.
