Focal Stack Image Compression Based on Basis-Quadtree Representation

doi:10.1109/TMM.2022.3169055

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Focal Stack Image Compression Based on Basis-Quadtree Representation

2023-01-01

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Kejun Wu

You Yang

Qiong Liu *

Xiaoping ZHANG (Xiao–Ping Zhang)

DOI：10.1109/TMM.2022.3169055

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Abstract

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In this paper, we propose an efficient compression scheme for focal stack images (FoSIs) based on a new basis-quadtree representation. In the new basis-quadtree representation, FoSIs are initially reorganized as co-located block groups in the depth dimension. In each group, selective basis blocks and adaptive quadtree partition are optimized to predict the focused or defocused co-located blocks by intra-group approximation. By solving a joint optimization problem, FoSIs can be efficiently represented by the optimal basis blocks, corresponding quadtree partition and approximation parameters, which will be compressed separately. Then, these basis blocks are stitched into several new frames (basis frames) according to their original locations and partition modes. Basis frames are compressed by our designed encoder, where the intra-group approximation is embedded into the high efficiency video coding (HEVC) encoder. Thus, the redundancies of basis blocks can be further eliminated. Finally, the approximation parameters are refined to suppress the amplified errors caused by introduced compression blur after basis frame coding. The refined parameters are compressed losslessly and multiplexed with the bitstream of the basis frames to ensure the reconstruction quality of FoSIs. Experiments on 12 test sequences demonstrate that the proposed scheme can obtain higher coding performance than the state-of-the-art comparison schemes. Specifically, the proposed scheme achieves up to 5.23 dB PSNR gains and 71.59% bitrate savings over the HEVC baseline scheme on sequences I03 and I05, respectively.

Keywords:

Image coding

Encoding

Redundancy

Predictive models

Optimization

Visualization

Three-dimensional displays

Focal stack images

image representation

image compression

video coding