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- Ahmad, Waqas, et al.
(författare)
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Computationally Efficient Light Field Image Compression Using a Multiview HEVC Framework
- 2019
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Ingår i: IEEE Access. - 2169-3536. ; 7, s. 143002-143014
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Tidskriftsartikel (refereegranskat)abstract
- The acquisition of the spatial and angular information of a scene using light eld (LF) technologies supplement a wide range of post-processing applications, such as scene reconstruction, refocusing, virtual view synthesis, and so forth. The additional angular information possessed by LF data increases the size of the overall data captured while offering the same spatial resolution. The main contributor to the size of captured data (i.e., angular information) contains a high correlation that is exploited by state-of-the-art video encoders by treating the LF as a pseudo video sequence (PVS). The interpretation of LF as a single PVS restricts the encoding scheme to only utilize a single-dimensional angular correlation present in the LF data. In this paper, we present an LF compression framework that efciently exploits the spatial and angular correlation using a multiview extension of high-efciency video coding (MV-HEVC). The input LF views are converted into multiple PVSs and are organized hierarchically. The rate-allocation scheme takes into account the assigned organization of frames and distributes quality/bits among them accordingly. Subsequently, the reference picture selection scheme prioritizes the reference frames based on the assigned quality. The proposed compression scheme is evaluated by following the common test conditions set by JPEG Pleno. The proposed scheme performs 0.75 dB better compared to state-of-the-art compression schemes and 2.5 dB better compared to the x265-based JPEG Pleno anchor scheme. Moreover, an optimized motionsearch scheme is proposed in the framework that reduces the computational complexity (in terms of the sum of absolute difference [SAD] computations) of motion estimation by up to 87% with a negligible loss in visual quality (approximately 0.05 dB).
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