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- Ahmad, Waqas, et al.
(author)
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Shearlet Transform-Based Light Field Compression under Low Bitrates
- 2020
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In: IEEE Transactions on Image Processing. - : IEEE. - 1057-7149 .- 1941-0042. ; 29, s. 4269-4280
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Journal article (peer-reviewed)abstract
- Light field (LF) acquisition devices capture spatial and angular information of a scene. In contrast with traditional cameras, the additional angular information enables novel post-processing applications, such as 3D scene reconstruction, the ability to refocus at different depth planes, and synthetic aperture. In this paper, we present a novel compression scheme for LF data captured using multiple traditional cameras. The input LF views were divided into two groups: key views and decimated views. The key views were compressed using the multi-view extension of high-efficiency video coding (MV-HEVC) scheme, and decimated views were predicted using the shearlet-transform-based prediction (STBP) scheme. Additionally, the residual information of predicted views was also encoded and sent along with the coded stream of key views. The proposed scheme was evaluated over a benchmark multi-camera based LF datasets, demonstrating that incorporating the residual information into the compression scheme increased the overall peak signal to noise ratio (PSNR) by 2 dB. The proposed compression scheme performed significantly better at low bit rates compared to anchor schemes, which have a better level of compression efficiency in high bit-rate scenarios. The sensitivity of the human vision system towards compression artifacts, specifically at low bit rates, favors the proposed compression scheme over anchor schemes. The proposed compression scheme performed significantly better at low bit rates compared to anchor schemes, which have a better level of compression efficiency in high bit-rate scenarios. The sensitivity of the human vision system towards compression artifacts, specifically at low bit rates, favors the proposed compression scheme over anchor schemes. The proposed compression scheme performed significantly better at low bit rates compared to anchor schemes, which have a better level of compression efficiency in high bit-rate scenarios. The sensitivity of the human vision system towards compression artifacts, specifically at low bit rates, favors the proposed compression scheme over anchor schemes.
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| 2. |
- Ahmad, Waqas, et al.
(author)
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Shearlet Transform Based Prediction Scheme for Light Field Compression
- 2018
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Conference paper (peer-reviewed)abstract
- Light field acquisition technologies capture angular and spatial information ofthe scene. The spatial and angular information enables various post processingapplications, e.g. 3D scene reconstruction, refocusing, synthetic aperture etc at theexpense of an increased data size. In this paper, we present a novel prediction tool forcompression of light field data acquired with multiple camera system. The captured lightfield (LF) can be described using two plane parametrization as, L(u, v, s, t), where (u, v)represents each view image plane coordinates and (s, t) represents the coordinates of thecapturing plane. In the proposed scheme, the captured LF is uniformly decimated by afactor d in both directions (in s and t coordinates), resulting in a sparse set of views alsoreferred to as key views. The key views are converted into a pseudo video sequence andcompressed using high efficiency video coding (HEVC). The shearlet transform basedreconstruction approach, presented in [1], is used at the decoder side to predict thedecimated views with the help of the key views.Four LF images (Truck, Bunny from Stanford dataset, Set2 and Set9 from High DensityCamera Array dataset) are used in the experiments. Input LF views are converted into apseudo video sequence and compressed with HEVC to serve as anchor. Rate distortionanalysis shows the average PSNR gain of 0.98 dB over the anchor scheme. Moreover, inlow bit-rates, the compression efficiency of the proposed scheme is higher compared tothe anchor and on the other hand the performance of the anchor is better in high bit-rates.Different compression response of the proposed and anchor scheme is a consequence oftheir utilization of input information. In the high bit-rate scenario, high quality residualinformation enables the anchor to achieve efficient compression. On the contrary, theshearlet transform relies on key views to predict the decimated views withoutincorporating residual information. Hence, it has inherit reconstruction error. In the lowbit-rate scenario, the bit budget of the proposed compression scheme allows the encoderto achieve high quality for the key views. The HEVC anchor scheme distributes the samebit budget among all the input LF views that results in degradation of the overall visualquality. The sensitivity of human vision system toward compression artifacts in low-bitratecases favours the proposed compression scheme over the anchor scheme.
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| 3. |
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| 4. |
- Schwarz, Sebastian, 1980-
(author)
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Depth Map Upscaling for Three-Dimensional Television : The Edge-Weighted Optimization Concept
- 2012
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Licentiate thesis (other academic/artistic)abstract
- With the recent comeback of three-dimensional (3D) movies to the cinemas, there have been increasing efforts to spread the commercial success of 3D to new markets. The possibility of a 3D experience at home, such as three-dimensional television (3DTV), has generated a great deal of interest within the research and standardization community.A central issue for 3DTV is the creation and representation of 3D content. Scene depth information plays a crucial role in all parts of the distribution chain from content capture via transmission to the actual 3D display. This depth information is transmitted in the form of depth maps and is accompanied by corresponding video frames, i.e. for Depth Image Based Rendering (DIBR) view synthesis. Nonetheless, scenarios do exist for which the original spatial resolutions of depth maps and video frames do not match, e.g. sensor driven depth capture or asymmetric 3D video coding. This resolution discrepancy is a problem, since DIBR requires accordance between the video frame and depth map. A considerable amount of research has been conducted into ways to match low-resolution depth maps to high resolution video frames. Many proposed solutions utilize corresponding texture information in the upscaling process, however they mostly fail to review this information for validity.In the strive for better 3DTV quality, this thesis presents the Edge-Weighted Optimization Concept (EWOC), a novel texture-guided depth upscaling application that addresses the lack of information validation. EWOC uses edge information from video frames as guidance in the depth upscaling process and, additionally, confirms this information based on the original low resolution depth. Over the course of four publications, EWOC is applied in 3D content creation and distribution. Various guidance sources, such as different color spaces or texture pre-processing, are investigated. An alternative depth compression scheme, based on depth map upscaling, is proposed and extensions for increased visual quality and computational performance are presented in this thesis. EWOC was evaluated and compared with competing approaches, with the main focus was consistently on the visual quality of rendered 3D views. The results show an increase in both objective and subjective visual quality to state-of-the-art depth map upscaling methods. This quality gain motivates the choice of EWOC in applications affected by low resolution depth.In the end, EWOC can improve 3D content generation and distribution, enhancing the 3D experience to boost the commercial success of 3DTV.
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