Block-matching algorithm

About: Block-matching algorithm is a research topic. Over the lifetime, 9590 publications have been published within this topic receiving 165336 citations.

Phase-based video motion processing

Abstract: We introduce a technique to manipulate small movements in videos based on an analysis of motion in complex-valued image pyramids. Phase variations of the coefficients of a complex-valued steerable pyramid over time correspond to motion, and can be temporally processed and amplified to reveal imperceptible motions, or attenuated to remove distracting changes. This processing does not involve the computation of optical flow, and in comparison to the previous Eulerian Video Magnification method it supports larger amplification factors and is significantly less sensitive to noise. These improved capabilities broaden the set of applications for motion processing in videos. We demonstrate the advantages of this approach on synthetic and natural video sequences, and explore applications in scientific analysis, visualization and video enhancement.

Multirate 3-D subband coding of video

Abstract: We propose a full color video compression strategy, based on 3-D subband coding with camera pan compensation, to generate a single embedded bit stream supporting multiple decoder display formats and a wide, finely gradated range of bit rates. An experimental implementation of our algorithm produces a single bit stream, from which suitable subsets are extracted to be compatible with many decoder frame sizes and frame rates and to satisfy transmission bandwidth constraints ranging from several tens of kilobits per second to several megabits per second. Reconstructed video quality from any of these bit stream subsets is often found to exceed that obtained from an MPEG-1 implementation, operated with equivalent bit rate constraints, in both perceptual quality and mean squared error. In addition, when restricted to 2-D, the algorithm produces some of the best results available in still image compression. >

A novel unrestricted center-biased diamond search algorithm for block motion estimation

Abstract: The widespread use of block-based interframe motion estimation for video sequence compression in both MPEG and H.263 standards is due to its effectiveness and simplicity of implementation. Nevertheless, the high computational complexity of the full-search algorithm has motivated a host of suboptimal but faster search strategies. A popular example is the three-step search (TSS) algorithm. However, its uniformly spaced search pattern is not well matched to most real-world video sequences in which the motion vector distribution is nonuniformly biased toward the zero vector. Such an observation inspired the new three-step search (NTSS) which has a center-biased search pattern and supports a halfway-stop technique. It is faster on average, and gives better motion estimation as compared to the well-known TSS. Later, the four-step search (4SS) algorithm was introduced to reduce the average case from 21 to 19 search points, while maintaining a performance similar to NTSS in terms of motion compensation errors. We propose a novel unrestricted center-biased diamond search (UCBDS) algorithm which is more efficient, effective, and robust than the previous techniques. It has a best case scenario of only 13 search points and an average of 15.5 block matches. This makes UCBDS consistently faster than the other suboptimal block-matching techniques. This paper also compares the above methods in which both the processing speed and the accuracy of motion compensation are tested over a wide range of test video sequences.

New fast algorithms for the estimation of block motion vectors

Abstract: Two algorithms for block motion estimation that produce performance similar to that of exhaustive search but with computation reduced by a factor of 8 or 16 are presented. The algorithms are based on motion-field and pixel subsampling. A subsampled motion field is first determined by estimating the motion vectors for a fraction of the blocks. The motion vectors for these blocks are determined by using only a fraction of the pixels at any searched location and by alternating the pixel subsampling patterns with the searched locations. The subsampled motion field is then interpolated so that a motion vector is determined for each block of pixels. The algorithms are more robust than previously proposed fast algorithms and both can easily be combined with a hierarchical search strategy. One of the algorithms is fully compatible with MPEG-I. >

Adaptive rood pattern search for fast block-matching motion estimation

Abstract: We propose a novel and simple fast block-matching algorithm (BMA), called adaptive rood pattern search (ARPS), which consists of two sequential search stages: (1) initial search and (2) refined local search. For each macroblock (MB), the initial search is performed only once at the beginning in order to find a good starting point for the follow-up refined local search. By doing so, unnecessary intermediate search and the risk of being trapped into local minimum matching error points could be greatly reduced in long search case. For the initial search stage, an adaptive rood pattern (ARP) is proposed, and the ARP's size is dynamically determined for each MB, based on the available motion vectors (MVs) of the neighboring MBs. In the refined local search stage, a unit-size rood pattern (URP) is exploited repeatedly, and unrestrictedly, until the final MV is found. To further speed up the search, zero-motion prejudgment (ZMP) is incorporated in our method, which is particularly beneficial to those video sequences containing small motion contents. Extensive experiments conducted based on the MPEG-4 Verification Model (VM) encoding platform show that the search speed of our proposed ARPS-ZMP is about two to three times faster than that of the diamond search (DS), and our method even achieves higher peak signal-to-noise ratio (PSNR) particularly for those video sequences containing large and/or complex motion contents.