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首页> 外文期刊>Neurocomputing >Efficient recording and retrieval of complex digital Fresnel holograms based on the line partitioned autoassociative memory
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Efficient recording and retrieval of complex digital Fresnel holograms based on the line partitioned autoassociative memory

机译:基于行分区自动关联存储器的复杂数字菲涅耳全息图的高效记录和检索

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摘要

In this paper, a novel method for the recording and retrieval of multiple digital Fresnel holograms, each corresponding a three dimensional (3D) object scene, is presented. As the hologram is complex (composing of a real and an imaginary parts), and its data size is generally larger than the optical image it represents, a classical AAM required to record the holographic data is enormous even for a medium size hologram. In view of this, we first convert the hologram into a binary format with error diffusion (a process hereafter refer to as 'binarization'). Each row of the hologram is recorded in a sub-autoassociative memory (SAAM), resulting in a network that is over 4 orders of magnitude smaller in size than the use of a single, classical AAM for recording the hologram directly. Our proposed AAM is referred to as the line partitioned autoassociative memory (LP-AAM). Experimental results demonstrate that our proposed LP-AAM is effective in retrieving a binary hologram when a corrupted or noise contaminated version of it is presented. Subsequently, the retrieved binary hologram can be taken to reconstruct the pictorial content with a quality that is comparable to that represented by the original hologram before binarization. To our knowledge, this is the first time an autoassociative memory is developed for the handling of holographic images. (C) 2015 Elsevier B.V. All rights reserved.
机译:在本文中,提出了一种记录和检索多个数字菲涅耳全息图的新颖方法,每个全息图对应于三维(3D)物体场景。由于全息图是复杂的(由实部和虚部组成),并且其数据大小通常大于其表示的光学图像,因此即使对于中等大小的全息图,记录全息数据所需的经典AAM也是巨大的。鉴于此,我们首先将全息图转换为具有误差扩散的二进制格式(以下称为“二进制化”过程)。全息图的每一行都记录在一个亚自缔合存储器(SAAM)中,与使用单个经典AAM直接记录全息图相比,网络的尺寸要小4个数量级。我们提出的AAM被称为行分区自动关联内存(LP-AAM)。实验结果表明,当提出损坏的或受噪声污染的版本时,我们提出的LP-AAM可有效地检索二进制全息图。随后,取回的二进制全息图可以用来重建图片内容,其质量与二值化之前的原始全息图表示的质量相当。据我们所知,这是第一次开发用于图像处理的自动联想存储器。 (C)2015 Elsevier B.V.保留所有权利。

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