Weighted constraint stochastic gradient descent algorithm for computational holographic near-eye display

Holography, Diffractive Optics, and Applications XII(2022)

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摘要
Stochastic gradient descent (SGD) algorithm with weighted constraint strategy is proposed to solve the vortex stagnation problem in CGH optimization and improve the image quality for computational holographic near-eye display. The weighted constraint strategy includes weighted phase constraint and weighted amplitude constraint. The weighted phase constraint is used to smooth the phase profile of reconstructed field, which helps to solve the vortex stagnation problem caused by optical vortices and eliminate the speckles in reconstructed field. The weighted amplitude constraint is used to broaden the optimization space by introducing the amplitude freedom of non-signal region in the reconstructed field, which helps to further improve the image quality in the signal region. The weighted constraint SGD algorithm can ensure the stable convergence of CGH optimization and avoid the vortex stagnation, which helps to eliminate the speckles and improve the image quality for holographic near-eye display.
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关键词
Computer holography, holographic display, near-eye display, optimization, speckle, optical vortices
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