Fast block matching motion estimation algorithms for video compression

As the telecommunication technology grows in the modern era from internet to video conferencing, Video compression has become an avoidable feature in information broadcast and also in the entertainment media. In this thesis we compared a different block matching motion estimation algorithms to find the motion estimation with a rapid growth of multimedia information; when transmitting a large amount of data video coding standards have become crucial. Motion estimation ascertain to be the key to splendid performance in video coding by recover the temporal redundancy effectively between adjacent frames, so it has been widely used to popular video compression coding standards such as MPEG-2, MPEG-4 and recent video coding standards H.264 of video data for storage and transmission. So Based on the study of motion vector distribution from several commonly used test image sequences, a three step diamond search [TSDS]algorithm for fast block matching motion estimation is proposed in this paper .The performance of this algorithm is compared with other existing algorithms of basic full search [FS], three step search [TSS] and diamond search [DS] by means of error metrics and no of search points in this the simulation results shows that the proposed three step diamond search algorithm achieves close performance with that of diamond search [DS] and uses less no of search points than the three step search[TSS]. When compared with original diamond search [DS] algorithm, this algorithm requires less computation time and gives an improved performance

A novel hexagonal search algorithm for fast block matching motion estimation

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Hardware acceleration architectures for MPEG-Based mobile video platforms: a brief overview

This paper presents a brief overview of past and current hardware acceleration (HwA) approaches that have been proposed for the most computationally intensive compression tools of the MPEG-4 standard. These approaches are classified based on their historical evolution and architectural approach. An analysis of both evolutionary and functional classifications is carried out in order to speculate on the possible trends of the HwA architectures to be employed in mobile video platforms

Energy-efficient acceleration of MPEG-4 compression tools

We propose novel hardware accelerator architectures for the most computationally demanding algorithms of the MPEG-4 video compression standard-motion estimation, binary motion estimation (for shape coding), and the forward/inverse discrete cosine transforms (incorporating shape adaptive modes). These accelerators have been designed using general low-energy design philosophies at the algorithmic/architectural abstraction levels. The themes of these philosophies are avoiding waste and trading area/performance for power and energy gains. Each core has been synthesised targeting TSMC 0.09 μm TCBN90LP technology, and the experimental results presented in this paper show that the proposed cores improve upon the prior art

DC-image for real time compressed video matching

This chapter presents a suggested framework for video matching based on local features extracted from the DC-image of MPEG compressed videos, without full decompression. In addition, the relevant arguments and supporting evidences are discussed. Several local feature detectors will be examined to select the best for matching using the DC-image. Two experiments are carried to support the above. The first is comparing between the DC-image and I-frame, in terms of matching performance and computation complexity. The second experiment compares between using local features and global features regarding compressed video matching with respect to the DC-image. The results confirmed that the use of DC-image, despite its highly reduced size, it is promising as it produces higher matching precision, compared to the full I-frame. Also, SIFT, as a local feature, outperforms most of the standard global features. On the other hand, its computation complexity is relatively higher, but it is still within the real-time margin which leaves a space for further optimizations that can be done to improve this computation complexity

Video matching using DC-image and local features

This paper presents a suggested framework for video matching based on local features extracted from the DCimage of MPEG compressed videos, without decompression. The relevant arguments and supporting evidences are discussed for developing video similarity techniques that works directly on compressed videos, without decompression, and especially utilising small size images. Two experiments are carried to support the above. The first is comparing between the DC-image and I-frame, in terms of matching performance and the corresponding computation complexity. The second experiment compares between using local features and global features in video matching, especially in the compressed domain and with the small size images. The results confirmed that the use of DC-image, despite its highly reduced size, is promising as it produces at least similar (if not better) matching precision, compared to the full I-frame. Also, using SIFT, as a local feature, outperforms precision of most of the standard global features. On the other hand, its computation complexity is relatively higher, but it is still within the realtime margin. There are also various optimisations that can be done to improve this computation complexity