Compensation and Improvement of Intensity and Distribution in Reconstructed Image Using Adaptive Optics in Holographic Data Storage

概要

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We applied a genetic algorithm to adaptive optics to improve the intensity and distribution of reconstructed images in holographic data storage. This is a kind of combinatorial optimisation. In holographic data storage, the photopolymer recording medium shrinks during light curing and this shrinkage distorts the recorded interference fringes, which degrades the reconstructed data images. Although it is possible to compensate for the degradation in the reconstructed image by using adaptive optics, it has been difficult to compensate for the shrinkage distortion by using normal feedback control because the relationship between the reconstructed image and deformable mirror input is nonlinear. With our method, the inverse variance coefficient in a reconstructed image with bits that are all "1" increased from 10.3 to 14.7 dB, an improvement of 4.4 dB. Moreover, the intensity average of the reconstructed image with compensation was 1.7 times higher than the average without compensation. These results show that the combination of adaptive optics and a genetic algorithm is very effective for improving reconstructed images.
Published by the Japan Society of Applied Physics through the Institute of Pure and Applied Physicsの論文
2008-07-25