Motion Estimation (ME) is an important part of most video encoding systems, since it could significantly affect the output quality of an encoded sequence. Unfortunately this feature requires a significant part of the encoding time especially when using the straightforward Full Search (FS) algorithl In this paper a new algorithm is presented named as the Predictive Motion Vector Field Adaptive Search Technique (PMVFAST), which significantly outperforms most if not all other previously proposed algorithms in terms of Speed Up performance. In addition, the output quality of the encoded sequence in terms of PSNR is similar to that of the Full Search algorithm. The proposed algorithm relies mainly upon very robust and reliable predictive techniques and early termination criteria, which make use of parameters adapted to the local characteristics of a frame. Our experiments verify the superiority of the proposed algorithm, not only versus several other well-known fast algorithms, but also in many cases versus even the Full Search algorithm.

Motion Estimation (ME) for video coding has taken an entirely different direction with the emergence of zonal algorithms. These algorithms made it possible to significantly reduce, if not almost eliminate, the tremendous computational overhead of motion estimation that was incurred in a video encoding system, while having little if any loss in quality. In this paper we further improve on these algorithms with the introduction of the Enhanced Predictive Zonal Search Algorithm (EPZS). By considering an additional set of predictors, improving the thresholding process, and simplifying the search pattern employed by these algorithms, we not only manage in achieving better output quality, but also reduce complexity of the motion estimation process even further. Our algorithm was compared with the algorithms accepted in the Optimization Model 1.0 of MPEG-4, and our simulations prove its outright superiority versus the existing algorithms. Furthermore we present a 3Dimensional implementation of EPZS, which can be easily applied in the case of multiple frame motion estimation (ITU H.263++ and H.26L).

This paper proposes a method for progressive lossy-to-lossless compression of four-dimensional (4-D) medical images (sequences of volumetric images over time) by using a combination of three-dimensional (3-D) integer wavelet transform (IWT) and 3-D motion compensation. A 3-D extension of the set-partitioning in hierarchical trees (SPIHT) algorithm is employed for coding the wavelet coefficients. To effectively exploit the redundancy between consecutive 3-D images, the concepts of key and residual frames from video coding is used. A fast 3-D cube matching algorithm is employed to do motion estimation. The key and the residual volumes are then coded using 3-D IWT and the modified 3-D SPIHT. The experimental results presented in this paper show that our proposed compression scheme achieves better lossy and lossless compression performance on 4-D medical images when compared with JPEG-2000 and volumetric compression based on 3-D SPIHT.

There are several parts of the video encoding process that can be optimized for high quality, high compression ratio and fast encoding speed. In this paper we focus on some of these encoder optimization issues. We first study motion estimation, a computationally intensive part of encoding, and propose efficient algorithms based on exploiting spatially correlated motion, that perform well in terms of speed, quality and the bit rate for different kinds of motion sequences as well as picture formats. We extend our motion estimation algorithms to find motion vectors for sub-parts of a block, as allowed for in the H.263 and MPEG-4 standards. We study the one-four motion vector decision and propose an efficient two-tier decision strategy. We then study the error measurement or the measure of similarity that is an important parameter for motion estimation as well as the mode decision. We introduce a new error measurement that can improve the mode decision significantly. Furthermore for certain motion estimation strategies, this new measurement can also improve the bit rate resulting from a better motion estimation. Another issue that we address in this paper is the estimation of delta motion vectors in the H.263 and the MPEG-4 standards. We have implemented these optimizations in a H.263 framework and the results are encouraging. I.

In this paper a new fast motion estimation algorithm is presented. The algorithm, named as Predictive Diamond Search, is actually based on the Diamond Search (DS) algorithm, which was recently adopted inside the MPEG-4 standard. The DS algorithm, even though faster than most known algorithms, was found not to be very robust in terms of quality for several sequences. By introducing a new predictive criterion and some additional steps in DS, our simulation results show that the proposed algorithm manages to have similar complexity with the DS algorithm, while having superior and more robust quality, similar to that of the Full Search (FS) algorithm.

Four-dimensional (4D) medical images, which are sequences of volume images over time, are represented by a great volume of information. One set of 4D medical images can easily take up hundreds of megabytes of storage volume. In this paper, we present a technique for compressing 4D medical images by combining motion compensation and lossless/near-lossless image encoding. Our technique incorporates a new fast 3D cube match algorithm that effectively exploits the redundancy between frames. The proposed scheme is validated by experiments on 4D cardiac images.

Abstract – Motion estimation plays an important role in modern video coders. In such coders, motion is estimated using a block matching algorithm that estimates the amount of motion on a blockby-block basis. A full search technique for finding the best matching blocks delivers good accuracy but is usually not practical due to its high computational complexity. In this paper, a novel fast blockbased motion estimation algorithm is proposed. This algorithm uses an efficient projection framework which bounds the distance between a template block and candidate blocks. Fast projection is performed with a family of highly efficient filter kernels – the Gray Code Kernels – using only 2 operations per pixel for each filter kernel. The projection framework is combined with a rejection scheme which allows rapid rejection of candidate blocks that are distant from the template block. Experiments show that the proposed algorithm significantly outperforms popular fast motion estimation algorithms, such as three-step search and diamond search. In addition, the tradeoff between computational complexity and quality of results could be easily controlled in the proposed algorithm, thus it enables adaptivity to image content.

In block motion estimation, search pattern with different shape or size has very important impact on search speed and distortion performance. In this paper, we propose a novel algorithm using hexagon-based search (HEXBS) pattern for fast block motion estimation. The proposed HEXBS algorithm may find any motion vector with fewer search points than the diamond search (DS) algorithm. The speedup gain of the HEXBS method over the DS algorithm is more striking for finding large motion vectors. Experimental results substantially justify the fastest performance of the HEXBS algorithm compared with several other popular fast algorithms. 1.

Motion estimation and motion compensation comprise one of the most important compression methods for video communications. We propose a low-power design of a motion estimation block for a low bit-rate video codec standard H.263. Since the motion estimation is computationally intensive to result in large power consumption, a low-power design is essential for portable or mobile systems. Our block employs the Four-Step Search (4SS) method as its primary algorithm. The design and the algorithm have been optimized to provide adequate results for low-quality video at low-power consumption. The model is developed in VHDL and synthesized using a 0.35 um CMOS library. Power consumption of both gate-level circuits and memory-accesses have been considered. Gatelevel simulation shows the proposed design offers a 38 % power reduction over a “baseline” implementation of a 4SS model and a 60 % power reduction over a baseline Three-Step Search (TSS) model. Power savings through reduction of memory access is 26 % over the TSS model and 32 % over the 4SS model. The total power consumption of the proposed motion estimation block ranges from 7- 9 mW and is dependent on the type of video being motion estimated.

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