15 research outputs found
Low computational complexity variable block size (VBS) partitioning for motion estimation using the Walsh Hadamard transform (WHT)
Variable Block Size (VBS) based motion estimation has
been adapted in state of the art video coding, such as
H.264/AVC, VC-1. However, a low complexity H.264/AVC
encoder cannot take advantage of VBS due to its power consumption
requirements. In this paper, we present a VBS partition
algorithm based on a binary motion edge map without
either initial motion estimation or Rate-Distortion (R-D)
optimization for selecting modes. The proposed algorithm
uses the Walsh Hadamard Transform (WHT) to create a binary
edge map, which provides a computational complexity
cost effectiveness compared to other light segmentation
methods typically used to detect the required region
Low complexity hardware oriented H.264/AVC motion estimation algorithm and related low power and low cost architecture design
制度:新 ; 報告番号:甲2999号 ; 学位の種類:博士(工学) ; 授与年月日:2010/3/15 ; 早大学位記番号:新525
Reconfigurable Architecture For H.264/avc Variable Block Size Motion Estimation Based On Motion Activity And Adaptive Search Range
Motion Estimation (ME) technique plays a key role in the video coding systems to achieve high compression ratios by removing temporal redundancies among video frames. Especially in the newest H.264/AVC video coding standard, ME engine demands large amount of computational capabilities due to its support for wide range of different block sizes for a given macroblock in order to increase accuracy in finding best matching block in the previous frames. We propose scalable architecture for H.264/AVC Variable Block Size (VBS) Motion Estimation with adaptive computing capability to support various search ranges, input video resolutions, and frame rates. Hardware architecture of the proposed ME consists of scalable Sum of Absolute Difference (SAD) arrays which can perform Full Search Block Matching Algorithm (FSBMA) for smaller 4x4 blocks. It is also shown that by predicting motion activity and adaptively adjusting the Search Range (SR) on the reconfigurable hardware platform, the computational cost of ME required for inter-frame encoding in H.264/AVC video coding standard can be reduced significantly. Dynamic Partial Reconfiguration is a unique feature of Field Programmable Gate Arrays (FPGAs) that makes best use of hardware resources and power by allowing adaptive algorithm to be implemented during run-time. We exploit this feature of FPGA to implement the proposed reconfigurable architecture of ME and maximize the architectural benefits through prediction of motion activities in the video sequences ,adaptation of SR during run-time, and fractional ME refinement. The implemented ME architecture can support real time applications at a maximum frequency of 90MHz with multiple reconfigurable regions. iv When compared to reconfiguration of complete design, partial reconfiguration process results in smaller bitstream size which allows FPGA to implement different configurations at higher speed. The proposed architecture has modular structure, regular data flow, and efficient memory organization with lower memory accesses. By increasing the number of active partial reconfigurable modules from one to four, there is a 4 fold increase in data re-use. Also, by introducing adaptive SR reduction algorithm at frame level, the computational load of ME is reduced significantly with only small degradation in PSNR (≤0.1dB)
ENHANCED COMPUTATION TIME FOR FAST BLOCK MATCHING ALGORITHM
Video compression is the process of reducing the amount of data required to represent digital video while preserving an acceptable video quality. Recent studies on video compression have focused on multimedia transmission, videophones, teleconferencing, high definition television (HDTV), CD-ROM storage, etc. The idea of compression techniques is to remove the redundant information that exists in the video sequences.
Motion compensated predictive coding is the main coding tool for removing temporal redundancy of video sequences and it typically accounts for 50-80% of the video encoding complexity. This technique has been adopted by all of the existing international video coding standards. It assumes that the current frame can be locally modelled as a translation of the reference frames. The practical and widely method used to carry out motion compensated prediction is block matching algorithm. In this method, video frames are divided into a set of non-overlapped macroblocks; each target macroblock of the current frame is compared with the search area in the reference frame in order to find the best matching macroblock. This will carry out displacement vectors that stipulate the movement of the macroblocks from one location to another in the reference frame. Checking all these locations is called full Search, which provides the best result. However, this algorithm suffers from long computational time, which necessitates improvement. Several methods of Fast Block Matching algorithm were developed to reduce the computation complexity.
This thesis focuses on two classifications: the first is called the lossless block matching algorithm process, in which the computational time required to determine the matching macroblock of the full search is decreased while the resolution of the predicted frames is the same as for the full search. The second is called the lossy block matching algorithm process, which reduces the computational complexity effectively but the search result’s quality is not the same as for the full search
A survey on video compression fast block matching algorithms
Video compression is the process of reducing the amount of data required to represent digital video while preserving an acceptable video quality. Recent studies on video compression have focused on multimedia transmission, videophones, teleconferencing, high definition television, CD-ROM storage, etc. The idea of compression techniques is to remove the redundant information that exists in the video sequences.
Motion compensation predictive coding is the main coding tool for removing temporal redundancy of video sequences and it typically accounts for 50–80% of video encoding complexity. This technique has been adopted by all of the existing International Video Coding Standards. It assumes that the current frame can be locally modelled as a translation of the reference frames. The practical and widely method used to carry out motion compensated prediction is block matching algorithm. In this method, video frames are divided into a set of non-overlapped macroblocks and compared with the search area in the reference frame in order to find the best matching macroblock. This will carry out displacement vectors that stipulate the movement of the macroblocks from one location to another in the reference frame. Checking all these locations is called Full Search, which provides the best result. However, this algorithm suffers from long computational time, which necessitates improvement. Several methods of Fast Block Matching algorithm are developed to reduce the computation complexity.
This paper focuses on a survey for two video compression techniques: the first is called the lossless block matching algorithm process, in which the computational time required to determine the matching macroblock of the Full Search is decreased while the resolution of the predicted frames is the same as for the Full Search. The second is called lossy block matching algorithm process, which reduces the computational complexity effectively but the search result's quality is not the same as for the Full Search
Motion correlation based low complexity and low power schemes for video codec
制度:新 ; 報告番号:甲3750号 ; 学位の種類:博士(工学) ; 授与年月日:2012/11/19 ; 早大学位記番号:新6121Waseda Universit
Algoritmo de estimação de movimento e sua arquitetura de hardware para HEVC
Doutoramento em Engenharia EletrotécnicaVideo coding has been used in applications like video surveillance, video
conferencing, video streaming, video broadcasting and video storage. In a
typical video coding standard, many algorithms are combined to compress a
video. However, one of those algorithms, the motion estimation is the most
complex task. Hence, it is necessary to implement this task in real time by
using appropriate VLSI architectures. This thesis proposes a new fast motion
estimation algorithm and its implementation in real time. The results show that
the proposed algorithm and its motion estimation hardware architecture out
performs the state of the art. The proposed architecture operates at a
maximum operating frequency of 241.6 MHz and is able to process
1080p@60Hz with all possible variables block sizes specified in HEVC
standard as well as with motion vector search range of up to ±64 pixels.A codificação de vídeo tem sido usada em aplicações tais como, vídeovigilância,
vídeo-conferência, video streaming e armazenamento de vídeo.
Numa norma de codificação de vídeo, diversos algoritmos são combinados
para comprimir o vídeo. Contudo, um desses algoritmos, a estimação de
movimento é a tarefa mais complexa. Por isso, é necessário implementar esta
tarefa em tempo real usando arquiteturas de hardware apropriadas. Esta tese
propõe um algoritmo de estimação de movimento rápido bem como a sua
implementação em tempo real. Os resultados mostram que o algoritmo e a
arquitetura de hardware propostos têm melhor desempenho que os existentes.
A arquitetura proposta opera a uma frequência máxima de 241.6 MHz e é
capaz de processar imagens de resolução 1080p@60Hz, com todos os
tamanhos de blocos especificados na norma HEVC, bem como um domínio de
pesquisa de vetores de movimento até ±64 pixels
Complexity adaptation in video encoders for power limited platforms
With the emergence of video services on power limited platforms, it is necessary to consider both performance-centric and constraint-centric signal processing techniques. Traditionally, video applications have a bandwidth or computational resources constraint or both. The recent H.264/AVC video compression standard offers significantly improved efficiency and flexibility compared to previous standards, which leads to less emphasis on bandwidth. However, its high computational complexity is a problem for codecs running on power limited plat- forms. Therefore, a technique that integrates both complexity and bandwidth issues in a single framework should be considered.
In this thesis we investigate complexity adaptation of a video coder which focuses on managing computational complexity and provides significant complexity savings when applied to recent standards. It consists of three sub functions specially designed for reducing complexity and a framework for using these sub functions; Variable Block Size (VBS) partitioning, fast motion estimation, skip macroblock detection, and complexity adaptation framework.
Firstly, the VBS partitioning algorithm based on the Walsh Hadamard Transform (WHT) is presented. The key idea is to segment regions of an image as edges or flat regions based on the fact that prediction errors are mainly affected by edges. Secondly, a fast motion estimation algorithm called Fast Walsh Boundary Search (FWBS) is presented on the VBS partitioned images. Its results outperform other commonly used fast algorithms. Thirdly, a skip macroblock detection algorithm is proposed for use prior to motion estimation by estimating the Discrete Cosine Transform (DCT) coefficients after quantisation. A new orthogonal transform called the S-transform is presented for predicting Integer DCT coefficients from Walsh Hadamard Transform coefficients. Complexity saving is achieved by deciding which macroblocks need to be processed and which can be skipped without processing. Simulation results show that the proposed algorithm achieves significant complexity savings with a negligible loss in rate-distortion performance. Finally, a complexity adaptation framework which combines all three techniques mentioned above is proposed for maximizing the perceptual quality of coded video on a complexity constrained platform