• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.9
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• pp.77-83
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• 1997

We present a fast adaptive block matching algorithm using variable search area and subsampling to estimate motion vector more exactly. In the presented method, the block is classified into one of three motion categories: zero motion vector block, medium-motion bolck or high-motion block according to mean absolute difference of the block. By the simulation, the computation amount of the presented methoe comparable to three step search algorithm and new three step search algorithm. In the fast image sequence, the PSNR of our algorithm increased more than TSS and NTSS, because our algorithm estimated motion vector more accurately.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.372-379
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• 2000

In this paper, we propose a fast variable-size block matching algorithm for motion estimation based on bit-pattern. Motion estimation in the proposed algorithm is performed after the representation of image sequence is transformed 8bit pixel values into 1bit ones depending on the mean value of search block, which brings a short searching time by reducing the computational complexity. Moreover, adaptive searching methods according to the motion information of the block make the procedure of motion estimation efficient by eliminating an unnecessary searching of low motion block and deepening a searching procedure in high motion block. Experimental results show that the proposed algorithm provides better performance-0.5dB PSNR improvement-than full search block matching algorithm with a fixed block size.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3C
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• pp.258-263
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• 2006

Each pixel in a matching block does not equally contribute to block matching and the matching error is greatly affected by image complexity. On the basis of the facts, this paper proposes a fast motion estimation algorithm using some sub-blocks selected by the image complexity. The proposed algorithm divides a matching block into 16 sub-blocks, computes the image complexity in every sub-block, executes partial block matching using some sub-blocks with large complexity, and detects a motion vector. The simulation results show that the proposed algorithm brings about negligible image degradation, but can reduce a large amount of computation in comparison with conventional algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.2007-2012
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• 2011

To reduce huge computation in the block matching, this paper proposes a fast block matching algorithm which limits search points in the search area. On the basis of two facts that most motion vectors are located in central part of search area and matching error is monotonic decreasing toward the best similar block, the proposed algorithm moves a matching pattern between steps by the one pixel, predicts the motion direction for the best similar block from similar blocks decided in previous steps, and limits movements of search points to ${\pm}45^{\circ}C$ on it. As a result, it could remove the needless search points and reduce the block matching computation. In comparison with the conventional similar algorithms, the proposed algorithm caused the trivial image degradation in images with fast motion but kept the equivalent image quality in images with normal motion, and it, meanwhile, reduced from about 20% to over 67% of the their block matching computation.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.633-644
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• 2004

In this paper, we notice that the original NTSS algorithm can be proposed as the NTSS-3 Level algorithm by the multi-resolution technique. The fast block matching algorithm affects the speed by the patten combination and this paper proposes the block matching algorithm in different levels by multi-resolution technique, quite different from the original NTSS Patten. The block matching algorithm requires the multi-candidate to reduce the occurrence of low-image quality by the local minima problem. The simulation result compared to FS shows search speed 16 times quicker, and the PSNR 0.11-0.12［dB］ gets improved Image quality compared to the original fast block matching algorithm NTSS, and the speed is improved up to 0.1 times for improved image by the search point portion.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7C
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• pp.946-953
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• 2004

Fast search and conventional boolean matching motion estimation algorithms reduce computational complexity and data processing time but this algorithms have disadvantages that is difficult of implementation of hardware because of high control overhead and that is less performance than Full search Algorithm(FA). This paper present new all binary block matching algorithm, called Bit Converted All Binary Block Matching(BC-ABBM). Proposed algorithm have performance closed to the FA by boolean only block matching that may be very efficiently implemented in hardware for low bit rate video communication. Simulation results show that the PSNR of the proposed algorithm is about 0.04dB loss than FA but is about 0.6 ∼ 1.4dB gain than fast search algorithm and conventional boolean matching algorithm.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.2
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• pp.211-219
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• 1988

In this paper effective block matching algorithms are proposed to find the motion vector. There are two approaches to the estimation of the motion vector in MCC (motion compensated coding), i.e.pel(pixel element) recursive algorithm and block matching algorithm. The search algorithm in this paper is based on the block matching method. The advantage of this algorithm is the reduction of the computation time. In order to reduce the computation time, three mathods are proposed in this paper. These new algorithms are faster than other methods. Compared with the three step algorithm by Koga et al., the average ratio of the computational savings obtained from the proposed algorithm is about 3-4.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.39-42
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• 2000

Motion estimation plays an important role for video coding. In this paper, we derive optimal search patterns for fast block matching motion estimation. By analyzing the block matching algorithm as a function of block shape and size, we can find an optimal search pattern for initial motion estimation. The proposed idea, which has been verified experimentally by computer simulations, can provide an analytical basis for the current MPEG-2 proposals. In order to choose a more compact search pattern for BMA, we exploit the statistical relationship between the motion and the frame difference of each block.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.295-298
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• 2002

This paper presents a fast block-matching algorithm to improve the conventional Three-Step Search (TSS) based method. The proposed Comparison Fast Block Matching Algorithm (CFBMA) begins with DAB for adaptive search range to choose searching method, and searches a part of search window that has high possibility of motion vector like other partial search algorithms. The CFBMA also considers the opposite direction to reduce local minimum, which is ignored in almost conventional based partial search algorithms. CFBMA uses the summation half-stop technique to reduce the computational load. Experimental results show that the proposed algorithm achieves the high computational complexity compression effect and very close or better image quality compared with TSS, SES, NTSS based partial search algorithms.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.43-46
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• 2000

In this paper, we propose a fast adaptive diamond search algorithm(FADS) for block matching motion estimation. Fast motion estimation algorithms reduce the computational complexity by using the UESA (Unimodal Error Search Assumption) that the matching error monotonically increases as the search moves away from the global minimum error. Recently many fast BMAs(Block Matching Algorithms) make use of the fact that the global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the adjacent blocks. We change the origin of search window according to the spatially adjacent motion vectors and their MAE(Mean Absolute Error). The computer simulation shows that the proposed algorithm has almost the same computational complexity with UCBDS(Unrestricted Center-Biased Diamond Search)〔1〕, but enhance PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS(Full Search), even for the large motion case, with half the computational load.