Three-dimensional holoscopic image-coding scheme using a sparse viewpoint image array and disparities

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.