An Investigation of Block Searching Algorithms for Video Frame Codecs

Block matching is the most computationally demanding aspect of the video encoding process. In many applications real-time video encoding is desired and therefore it is important that the encoding is fast. Also where handheld devices such as a PDA or mobile phone are concerned a less computationally intensive algorithm means a simpler processor can be used which saves on hardware costs and also extends battery life. An optimised algorithm also allows these devices to be used in low bandwidth wireless networks. The challenge is to decrease the computational load on the system without compromising the quality of the video stream too much, thus enabling easier and less expensive implementations of real-time encoding. This thesis appraises some of the principal Block Search Algorithms used in Video compression today. This work follows on from the work of Aroh Barjatya who implemented 7 common Block Search Algorithms to predict P-frames in MATLAB. Three further hybrid DS algorithms are implemented in MATLAB. Additional code is added to produce plots of the main metrics and to calculate some statistics such as Average Searching Points, Average PSNR and the Speed Improvement Ratio with respect to the Diamond Search and the Exhaustive Search. For a comparative analysis with previous studies 3 standard industry test sequences are used. The first sequence, Miss America is a typical videoconferencing scene with limited object motion and a stationary background. The second sequence, Flower Garden consists mainly of stationary objects, but with a fast camera panning motion. The third sequence, Football contains large local object motion. The performance of the 3 implemented algorithms were assessed by the aforementioned statistics. Simulation results showed that the NCDS was the fastest algorithm amongst the 3 hybrid DS algorithms simulated. A speedup ranging from 10% for the complex motion sequence Flower Garden to nearly 54% for the low motion video conferencing sequence Miss America was recorded. All 3 algorithms performed very competitively in terms of PSNR compared to the DS even though they use a lower number of search points on average. It was shown that the NCDS has marginally worse PSNR performance than the DS compared to the other 2 algorithms – the highest being a drop in PSNR of 0.680dB for the Flower Garden sequence. However, the speed improvements for NCDS are quite substantial and thus would justify its use over the DS. The results from the implementation concurred with the literature therefore validating the implementation. The implementation was used as a guide in nominating a ‘robust’ Block Search Algorithm. When the DS, CDS, SCDS and the NCDS were compared with ARPS it was shown that ARPS generally gave both higher PSNR and higher search speed for all 3 sequences. The reason for the good performance of ARPS is that it quickly directs the search into the local region of the global minimum by calculating the Predicted Motion Vector. The minimum error from a rood pattern of nodes is found and then a final refined search calculates the motion vector. Simulation results showed that ARPS was the best algorithm amongst the 10 algorithms simulated from the point of view of speed (lowest number of search points used per macroblock) and video quality (PSNR). For real-time encoding of video the best fast block motion algorithm to advise is ARPS

Optimization of the motion estimation for parallel embedded systems in the context of new video standards

15 pagesInternational audienceThe effciency of video compression methods mainly depends on the motion compensation stage, and the design of effcient motion estimation techniques is still an important issue. An highly accurate motion estimation can significantly reduce the bit-rate, but involves a high computational complexity. This is particularly true for new generations of video compression standards, MPEG AVC and HEVC, which involves techniques such as different reference frames, sub-pixel estimation, variable block sizes. In this context, the design of fast motion estimation solutions is necessary, and can concerned two linked aspects: a high quality algorithm and its effcient implementation. This paper summarizes our main contributions in this domain. In particular, we first present the HME (Hierarchical Motion Estimation) technique. It is based on a multi-level refinement process where the motion estimation vectors are first estimated on a sub-sampled image. The multi-levels decomposition provides robust predictions and is particularly suited for variable block sizes motion estimations. The HME method has been integrated in a AVC encoder, and we propose a parallel implementation of this technique, with the motion estimation at pixel level performed by a DSP processor, and the sub-pixel refinement realized in an FPGA. The second technique that we present is called HDS for Hierarchical Diamond Search. It combines the multi-level refinement of HME, with a fast search at pixel-accuracy inspired by the EPZS method. This paper also presents its parallel implementation onto a multi-DSP platform and the its use in the HEVC context

An FPGA Implementation of HW/SW Codesign Architecture for H.263 Video Coding

Chapitre 12 http://www.intechopen.com/download/pdf/pdfs_id/1574

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

An efficient search strategy for block motion estimation using image features

2001-2002 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Adaptive fast block-matching algorithm by switching search patterns for sequences with wide-range motion content

[[abstract]]Content with rapid, moderate, and slow motion is frequently mixed together in real video sequences. Until now, no fast block-matching algorithm (FBMA), including the well-known three-step search (TSS), the block-based gradient descent search (BBGDS), and the diamond search (DS), can efficiently remove the temporal redundancy of sequences with wide range motion content. This paper proposes an adaptive FBMA, called A-TDB, to solve this problem. Based on the characteristics of a proposed predicted profit list, the A-TDB can adaptively switch search patterns among the TSS, DS, and BBGDS, according to the motion content. Experimental results reveal that the A-TDB successfully adopts the search patterns to remove the temporal redundancy of sequences with slow, moderate and rapid motion content.[[fileno]]203021101000

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

Fast implementations of block motion estimation algorithms in video encoders

This research is aimed at designing and implementing novel fast algorithms for speeding up the encoding process. The objective of this study was to come up with algorithms which can estimate the data significantly faster than the existing algorithms, whilst ensuring acceptable video quality

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