Adaptive Multi-Pattern Fast Block-Matching Algorithm Based on Motion Classification Techniques

Motion estimation is the most time-consuming subsystem in a video codec. Thus, more efficient methods of motion estimation should be investigated. Real video sequences usually exhibit a wide-range of motion content as well as different degrees of detail, which become particularly difficult to manage by typical block-matching algorithms. Recent developments in the area of motion estimation have focused on the adaptation to video contents. Adaptive thresholds and multi-pattern search algorithms have shown to achieve good performance when they success to adjust to motion characteristics. This paper proposes an adaptive algorithm, called MCS, that makes use of an especially tailored classifier that detects some motion cues and chooses the search pattern that best fits to them. Specifically, a hierarchical structure of binary linear classifiers is proposed. Our experimental results show that MCS notably reduces the computational cost with respect to an state-of-the-art method while maintaining the qualityPublicad

HDS, a real-time multi-DSP motion estimator for MPEG-4 H.264 AVC high definition video encoding

International audienceH.264 AVC video compression standard achieves high compression rates at the cost of a high encoder complexity. The encoder performances are greatly linked to the motion estimation operation which requires high computation power and memory bandwidth. High definition context magnifies the difficulty of a real-time implementation. EPZS and HME are two well-known motion estimation algorithms. Both EPZS and HME are implemented in a DSP and their performances are compared in terms of both quality and complexity. Based on these results, a new algorithm called HDS for Hierarchical Diamond Search is proposed. HDS motion estimation is integrated in a AVC encoder to extract timings and resulting video qualities reached. A real-time DSP implementation of H.264 quarter-pixel accuracy motion estimation is proposed for SD and HD video format. Furthermore HDS characteristics make this algorithm well suited for H.264 SVC real-time encoding applications

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

New Fast Block Matching Algorithm Using New Hybrid Search Pattern And Strategy To Improve Motion Estimation Process In Video Coding Technique

Up until today, video compression algorithm has been applied in various video applications ranging from video conferencing to video telephony. Motion Estimation or ME is deemed as one of the effective and popular techniques in video compression. As one of its techniques, the Block Matching Algorithm or BMA is widely employed in majority of well-known video codes due to its simplicity and high compression efficiency. As such, it is crucial to find different approaches of fast BMAs as the simplest and straightforward BMA is not a good fit for implementation of real-time video coding because of its high computational complexity. The aims for this study is to develop and design a new hybrid search pattern and strategy for new fast BMAs that can further improve the ME process in terms of estimation accuracy and video image quality, searching speed and computational complexity. There are 6 main designs that the algorithms proposed namely the Orthogonal-Diamond Search Algorithm with Small Diamond Search Pattern (ODS-SDSP), the Orthogonal-Diamond Search Algorithm with Large Diamond Search Pattern (ODS-LDSP), the Diamond-Orthogonal Search Algorithm with Small Diamond Pattern (DOS-SDSP), the Diamond-Orthogonal Search Algorithm with Large Diamond Pattern (DOS-LDSP), the Modified Diamond-Orthogonal Search Algorithm with Small Diamond Pattern (MDOS-SDSP), and the Modified Diamond-Orthogonal Search Algorithm with Large Diamond Pattern (MDOS-LDSP). These 6 algorithms are divided into 3 main methods namely Method A, Method B, and Method C depending on their search patterns and strategies. The first method involves the manipulation of the diamond pattern in the process, the second method includes the manipulation of the orthogonal steps, and lastly, the third method is the modified version of the second method to improve the performances of the algorithms. Evaluation is based on the algorithm performances in terms of the search points needed to find the final motion vector, the Peak-Signal to Noise Ratio (PSNR) of the algorithms, and the runtime performance of algorithm simulations. The result shows that the DOS-SDSP algorithm has the lowest search points with only 1.7341, 4.9059 and 4.0230 for each motion’s content respectively; meanwhile all the algorithms acquired similar and close PSNR values for all types of motion contents. As for simulation runtime, the results show that Method B has the least simulation runtime and Method C has the highest simulation runtime compared to others for all video sequences. The finding suggests that an early termination technique should be implemented at the early stage of the process, and mixing the selection of the mode is able to improve the algorithm performances. Therefore, it can be concluded that Method B gives the best performance in terms of search points reduction and simulation runtime while Method C yields the best for PSNR values for all types of motion contents

A new fast motion estimation algorithm using hexagonal subsampling pattern and multiple candidates search

In this paper we present a fast algorithm to reduce the computational complexity of block motion estimation. The reduction is obtained from the use of a new hexagonal subsampling pattern and the domain decimation method introduced by Cheng and Chan (see Proc. IEEE ICASSP, vol.4, p.2313, 1996). The multiple candidates search method is also introduced to improve the robustness of the algorithm. Computer simulation shows that the performance is very close to that of the full search.published_or_final_versio

Low-Complexity Context-Based Motion Compensation for VLBR Video Encoding

A significant improvement of block-based motion estimation strategies is presented, which provides fast computation and very low bitrate coding. For each block, a spatio-temporal context is defined based on nearest neighbors in the current and previous frames, and a prediction list is built. Then, the best matching vector within the list is chosen as an estimation of the block motion. Since coder and decoder are synchronous, only the index of the selected vector is needed at the decoder to reconstruct the motion field. To avoid the propagation of the error, an additional correction vector can be sent when prediction error exceeds a threshold. Furthermore, bitrate saving is achieved through an adaptive sorting of the prediction list of each block, which allows to reduce the entropy of the motion indexes. Tests demonstrate that the proposed method ensures a speed up over 1:200 as compared to full search, and a coding gain above 2, with a negligible loss of accuracy. This allows real-time implementation of VLBR software video coders on conventional PC platforms