Threshold-free pattern-based low bit rate video coding
- Authors: Paul, Manoranjan , Murshed, Manzur
- Date: 2008
- Type: Text , Conference paper
- Relation: 2008 15th IEEE International Conference on Image Processing p. 1584-1587
- Full Text: false
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- Description: Pattern-based video coding (PVC) has already established its superiority over recent video coding standard H.264, at low bit rate because of an extra pattern-mode to segment out the arbitrary shape of the moving region within the macroblock (MB). To determine the pattern-mode, the PVC however uses three thresholds to reduce the number of MBs coded using the pattern- mode. By setting these content-sensitive thresholds to any predefined values, the technique risks ignoring some MBs that would otherwise be selected by the rate-distortion optimization function for this mode. Consequently, the ultimate achievable performance is sacrificed to save motion estimation times. In this paper, a novel PVC scheme is proposed by removing all thresholds to determine this mode and hence more efficient performance is achieved without knowing the content of the video sequences. To keep computational complexity in check, pattern motion is approximated from the motion vector of the MB. In addition, efficient pattern similarity metric and new Lagrangian multipliers are also developed. The experimental results confirm that this new scheme improves the image quality by at least 0.5 dB and 1.0 dB compared to the existing PVC and the H.264 respectively
A novel depth edge prioritization based coding technique to boost-UP HEVC performance
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2016
- Type: Text , Conference paper
- Relation: 2016 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)
- Full Text: false
- Reviewed:
- Description: In addition to the texture, multiview video employs the utilization of depth coding for the reconstruction of 3D video and Free viewpoint video. Standing on some texture-depth correlations, a number of methods in literature reuses texture motion vector for the corresponding depth coding to reduce encoding time by avoiding costly motion estimation process. However, texture similarity metric is not always equivalent to the corresponding depth similarity metric especially at edge levels. Since their approaches could not explicitly detect and encode acute edge motions of depth objects, eventually, could not reach the similar or improved rate-distortion (RD) performance against the High Efficiency Video Coding (HEVC) reference test model (HM). With a view to more accurate motion detection and modeling, the proposed technique exploits an extra Pattern Mode comprising a group of pattern templates (GPTs) with different rectangular and non-rectangular object shapes and edges compared to the existing HEVC block partitioning modes. Moreover, the proposed Pattern Mode only encodes the motion areas and skips the background areas. The experimental results show that the proposed technique could save 30% encoding time and improve average 0.1dB Bjontegard Delta peak signal-to-noise ratio (BD-PSNR) compared to the HM.
Improved depth coding for HEVC focusing on depth edge approximation
- Authors: Podder, Pallab , Paul, Manoranjan , Rahaman, Motiur , Murshed, Manzur
- Date: 2017
- Type: Text , Journal article , acceptedVersion
- Relation: Signal Processing: Image Communication Vol. 55, no. (2017), p. 80-92
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- Description: The latest High Efficiency Video Coding (HEVC) standard has greatly improved the coding efficiency compared to its predecessor H.264. An important share of which is the adoption of hierarchical block partitioning structures and an extended number of modes. The structure of existing inter-modes is appropriate mainly to handle the rectangular and square aligned motion patterns. However, they could not be suitable for the block partitioning of depth objects having partial foreground motion with irregular edges and background. In such cases, the HEVC reference test model (HM) normally explores finer level block partitioning that requires more bits and encoding time to compensate large residuals. Since motion detection is the underlying criteria for mode selection, in this work, we use the energy concentration ratio feature of phase correlation to capture different types of motion in depth object. For better motion modeling focusing at depth edges, the proposed technique also uses an extra pattern mode comprising a group of templates with various rectangular and non-rectangular object shapes and edges. As the pattern mode could save bits by encoding only the foreground areas and beat all other inter-modes in a block once selected, the proposed technique could improve the rate-distortion performance. It could also reduce encoding time by skipping further branching using the pattern mode and selecting a subset of modes using innovative pre-processing criteria. Experimentally it could save 29% average encoding time and improve 0.10 dB Bjontegaard Delta peak signal-to-noise ratio compared to the HM.
Efficient video coding using visual sensitive information for HEVC coding standard
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 75695-75708
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- Description: The latest high efficiency video coding (HEVC) standard introduces a large number of inter-mode block partitioning modes. The HEVC reference test model (HM) uses partially exhaustive tree-structured mode selection, which still explores a large number of prediction unit (PU) modes for a coding unit (CU). This impacts on encoding time rise which deprives a number of electronic devices having limited processing resources to use various features of HEVC. By analyzing the homogeneity, residual, and different statistical correlation among modes, many researchers speed-up the encoding process through the number of PU mode reduction. However, these approaches could not demonstrate the similar rate-distortion (RD) performance with the HM due to their dependency on existing Lagrangian cost function (LCF) within the HEVC framework. In this paper, to avoid the complete dependency on LCF in the initial phase, we exploit visual sensitive foreground motion and spatial salient metric (FMSSM) in a block. To capture its motion and saliency features, we use the dynamic background and visual saliency modeling, respectively. According to the FMSSM values, a subset of PU modes is then explored for encoding the CU. This preprocessing phase is independent from the existing LCF. As the proposed coding technique further reduces the number of PU modes using two simple criteria (i.e., motion and saliency), it outperforms the HM in terms of encoding time reduction. As it also encodes the uncovered and static background areas using the dynamic background frame as a substituted reference frame, it does not sacrifice quality. Tested results reveal that the proposed method achieves 32% average encoding time reduction of the HM without any quality loss for a wide range of videos.
Performance scalable motion estimation for video coding : An overview of current status and a promising approach
- Authors: Sorwar, Golam , Murshed, Manzur
- Date: 2013
- Type: Text , Book chapter
- Relation: Multimedia networking and coding Chapter 3 p. 50-75
- Full Text: false
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- Description: Motion estimation is one of the major bottlenecks in real-time performance scalable video coding applications due to high computational complexity of exhaustive search. To address this, researchers so far focused on low-complexity motion estimation and rate-distortion optimization in isolation. Proliferation of power-constrained handheld devices with image capturing capability has created demand for much smarter approach where motion estimation is integrated with rate control such that rate-distortion-complexity optimization can be effectively achieved. It is indeed crucial to provide such performance scalability in motion estimation to facilitate complexity management in such devices. This chapter presents an overview of motion estimation. Beginning with an introduction to the importance of motion estimation, it systematically examines various motion estimation techniques and their strengths and weaknesses, focussing primarily on block-based motion search. It then examines the limitation of the existing techniques in accommodating performance scalability, introduces a promising approach, Distance-dependent Thresholding Search (DTS) motion search, to fill in this gap, and concludes with future research directions in the field. The authors suggest that the content of the chapter will make a significant contribution and serve as a reference for multimedia signal processing research at postgraduate level.
A novel motion classification based intermode selection strategy for HEVC performance improvement
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2015
- Type: Text , Journal article
- Relation: Neurocomputing Vol. 173, no. Part 3 (2015), p. 1211-1220
- Relation: http://purl.org/au-research/grants/arc/DP130103670
- Full Text: false
- Reviewed:
- Description: High Efficiency Video Coding (HEVC) standard adopts several new approaches to achieve higher coding efficiency (approximately 50% bit-rate reduction) compared to its predecessor H.264/AVC with same perceptual image quality. Huge computational time has also increased due to the algorithmic complexity of HEVC compared to H.264/AVC. However, it is really a demanding task to reduce the encoding time while preserving the similar quality of the video sequences. In this paper, we propose a novel efficient intermode selection technique and incorporate into HEVC framework to predict motion estimation and motion compensation modes between current and reference blocks and perform faster inter mode selection based on three dissimilar motion types in divergent video sequences. Instead of exploring and traversing all the modes exhaustively, we merely select a subset of candidate modes and the final mode from the selected subset is determined based on their lowest Lagrangian cost function. The experimental results reveal that average encoding time can be downscaled by 40% with similar rate-distortion performance compared to the exhaustive mode selection strategy in HEVC.
- Description: High Efficiency Video Coding (HEVC) standard adopts several new approaches to achieve higher coding efficiency (approximately 50% bit-rate reduction) compared to its predecessor H.264/AVC with same perceptual image quality. Huge computational time has also increased due to the algorithmic complexity of HEVC compared to H.264/AVC. However, it is really a demanding task to reduce the encoding time while preserving the similar quality of the video sequences. In this paper, we propose a novel efficient intermode selection technique and incorporate into HEVC framework to predict motion estimation and motion compensation modes between current and reference blocks and perform faster inter mode selection based on three dissimilar motion types in divergent video sequences. Instead of exploring and traversing all the modes exhaustively, we merely select a subset of candidate modes and the final mode from the selected subset is determined based on their lowest Lagrangian cost function. The experimental results reveal that average encoding time can be downscaled by 40% with similar rate-distortion performance compared to the exhaustive mode selection strategy in HEVC. © 2015 Elsevier B.V.