7 June 2018 Three-dimensional holoscopic image-coding scheme using a sparse viewpoint image array and disparities
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Abstract
Three-dimensional (3-D) holoscopic imaging is a candidate promising 3-D technology that can overcome some drawbacks of current 3-D technologies. Due to the particular optical structure, a holoscopic image consists of an array of two-dimensional microimages (MIs) that represent different perspectives of the scene. To address the data-intensive characteristics and specific structure of holoscopic images, efficient coding schemes are of utmost importance for efficient storage and transmission. We propose a 3-D holoscopic image-coding scheme using a sparse viewpoint image (VI) array and disparities. In the proposed scheme, a holoscopic image is decomposed into a VI array totally and the VI array is sampled into a sparse VI array. To reconstruct the full holoscopic image, disparities between adjoining MIs are calculated. Based on the remainder set of VIs and disparities, a full holoscopic image is reconstructed and encoded as a reference frame for the coding of the full holoscopic image. As an outcome of the representation, we propose a multiview plus depth compression scheme for 3-D holoscopic images coding. Experimental results show that the proposed coding scheme can achieve an average of 51% bit-rate reduction compared with high efficiency video coding intracoding.
© 2018 SPIE and IS&T 1017-9909/2018/$25.00 © 2018 SPIE and IS&T
Ling Yang, Ping An, Deyang Liu, Ran Ma, and Liquan Shen "Three-dimensional holoscopic image-coding scheme using a sparse viewpoint image array and disparities," Journal of Electronic Imaging 27(3), 033030 (7 June 2018). https://doi.org/10.1117/1.JEI.27.3.033030
Received: 4 September 2017; Accepted: 8 May 2018; Published: 7 June 2018
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Cited by 1 scholarly publication.
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KEYWORDS
Image compression

3D image processing

Image quality

Image processing

Computer programming

3D image reconstruction

Imaging arrays

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