• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.397-405
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• 2003

In this paper, we propose an efficient motion estimation algorithm which can reduce computational complexity by using characteristics of wavelet coefficient in each subband while keeping about the same image quality as in using MRME(multiresolution motion estimation). In general, because of the high similarity between consecutive frames, we first decide whether the motion exists or not by just comparing MAD(mean absolute difference) between blocks with threshold in the lowest subbands of consecutive two frames. If it turns out that there is no motion in the lowest subband, we can also decide no motion exists in the higher subband. This is due to the characteristics of wavelet transform. Conversely, if we find any motion in the lowest subband, we can reduce computational complexity by estimating high subband motion vectors selectively according to the amount of computational complexity by estimating high subband motion vectors selectively according to the amount of energy in that subband. Experimental results are shown that algorithm suggested in this paper maintains about the same PSNR as MRME. However, the processing time was reduced about 30-50% compared with the MRME.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.999-1002
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• 2002

In this paper, we proposes an adaptive method for reducing the computational overhead of fine-to-coarse MRME at the finest resolution level by considering for the spatial and spectral characteristics between wavelet decomposition levels simultaneously. As we know, there is high correlation between the adjacent blocks and it can give the very important clue to estimate motion at finest level. So, in this paper, using the initial motion vector and the adjacent motion vector in the coarsest level, we determine the optimal direction that will be minimized the estimation error in the finest level. In that direction, we define the potential searching region within the full searching region that is caused to increase much computational overhead in the FtC method. Last, in that region, we process the efficient 2-step motion estimation. and estimate the motion vector at finest resolution level. And then, this determined motion vector is scaled to coarser resolutions. As simulation result, this method is similar to computational complexity of the CtF MRME method and very significantly reduces that of the FtC MRME method. In addition, they provide higher quality than CtF MRME, both visually and quantitatively

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.11b
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• pp.21-25
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• 1999

Wavelet transform decomposes a video frame into a set of subframes with different resolutions corresponding to different frequency bands. The block size of highest layer subframe is too small to estimate correct motion. To decrease this aperture problem in the approximation frame, multiresolution motion estimation (MRME) using hierarchical block matching is presented in this paper. In the multiresolution motion estimation approach, motion vectors in the subframes are estimated by the motion vectors in the approximation frame and are refined at each subframe. It reduces computational time in motion estimation. It is shown that our MRME approach has a superior performance than traditional MRME approaches.

• Journal of Broadcast Engineering
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• v.8 no.3
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• pp.297-305
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• 2003

In this paper, we propose a wavelet based fast motion estimation algorithm for video sequence encoding with very low bit-rate. By using one of properties oi wavelet transform, multi-resolution analysis(MRA) property and spatial Interpolation of an image, we are able to reduce both prediction error and computational complexity at the same time. Especially, by defining a significant block(SB) based on the differential information of wavelet coefficients between successive frames, the proposed algorithm makes up a defect of multi-resolution motion estimation(MRME) algorithm of increasing the number of motion vectors. As experimental results. we can reduce the computational load up to 70% but also improve PSNR up to about 0.1 ∼ 1.2 dB comparing with the MRME algorithm.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.12
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• pp.1878-1888
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• 1990

In this paper, the input-output interconnection method of the multi-valued signal processing circuit using perfect Shuffle technique and Kronecker product is discussed. Using this method, the design method of circuit of the multi-valued Reed-Muller expansions(MRME) to be used the multi-valued signal processing on finite field GF(p**m) is presented. The proposed input-output interconnection method is shown that the matrix transform is efficient and that the module structure is easy. The circuit design of MRME on FG(p**m) is realized following as` 1) contructing the baisc gates on GF(3) by CMOS T gate, 2) designing the basic cells to be implemented the transform and inverse transform matrix of MRME using these basic gates, 3) interconnecting these cells by the input-output interconnecting method of the multivalued signal processing circuits. Also, the circuit design of the multi-valued signal processing function on GF(3\ulcorner similar to Winograd algorithm of 3x3 array of DFT (discrete fourier transform) is realized by interconnection of Perfect Shuffle technique and Kronecker product. The presented multi-valued signal processing circuits that are simple and regular for wire routing and posses the properties of concurrency and modularity are suitable for VLSI.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.40-47
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• 2003

In this paper, we propose a new method for reducing the computational overhead of fine-to-coarse multi-resolution motion estimation (MRME) at the finest resolution level by searching for the region to consider motion vectors of the coarsest resolution subband. At this time, if half-pel accuracy motion estimation (HPAME) is used in the baseband where influence a lot of effect to the reconstructed image, we can have the motion vector exactly But, this method causes to higher computational overhead. So we suggest the method to the computational overhead by using selective interpolation. Experimental results show that the proposed algorithm gives better results than the traditional algorithms from image quality.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.87-95
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• 2003

This paper proposes an object detection algorithm using the Multiresolution Motion Estimation(MRME) in wavelet d야main. A existing motion estimation method has characteristics of motion estimation but it requires having computation. Motion estimation in higher resolution used the motion vector of the lower resolution with the MRME that has parent-child relationship on wavelet coefficients. This method reduces the search area of motion estimation in higher resolution and computational complexity. The computational complexity of the proposed method is about 40% of the existing method using 3-level Set Partitioning in Hierarchical Trees(SPIHT) wavelet transform. The experimental results with the proposed method showed about 11% decrease of Mean Absolute Difference(MAD) and gains able to precise tracking of object.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10B
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• pp.1813-1820
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• 2000

In this paper we proposed an efficient multiresolution motion estimation(MRME) algorithm using half-pixel accuracy motion estimation (HPAME) and characteristics of motion vectors in the baseband. Conventional MRME method needs exact motion vectors in the baseband because those are used as initial motion vectors in higher frequency subbands. Therefore the proposed method uses HPAME to estimate the motion vectors exactly in the baseband. Based on the characteristics of these motion vectors the motion vectors in the higher frequency subbands are selectively estimatied. That is motion vectors in the higher frequency subbands are estimated only for the blocks which have the half-pixel accuracy motion vectors in the baseband. In the proposed method by using HPAME in the baseband and selective motion estimation in the higher frequency subbands we can obtain reconstructed image with the similar quality with the conventional method though we reduce the computational complexity and the bit rate considerably.

• The KIPS Transactions:PartA
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• v.9A no.3
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• pp.271-280
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• 2002

In this paper, the input-output interconnection method of the multiple-valued signal processing circuit using Perfect Shuffle technique and Kronecker product is discussed. Using this method, the circuit design method of the multiple-valued Reed-Muller Expansions (MRME) which can process the multiple-valued signal easily on finite fields GF$(p^m)$ is presented. The proposed input-output interconnection methods show that the matrix transform is an efficient and the structures are modular. The circuits of multiple-valued signal processing of MRME on GF$(p^m)$ design the basic cells to implement the transform and inverse transform matrix of MRME by using two basic gates on GF(3) and interconnect these cells by the input-output interconnection technique of the multiple-valued signal processing circuits. The proposed multiple-valued signal processing circuits that are simple and regular for wire routing and possess the properties of concurrency and modularity are suitable for VLSI.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.110-120
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• 2003

In this paper, we propose a Multiresolution Motion Estimation(MRME) adapted to Low-Band-Shift(LBS) method in wavelet domain. To overcome shift-variant property on wavelet coefficients, the LBS was previously proposed. This method which is applied to reference frame in video coding technique, has superior performance in terms of rate-distortion characteristic. However, this method needs more memory and computational complexity. In this paper, The computational complexity of the proposed method(LBS-MRME) is about 15.6% of that of existing method at 3-level wavelet transform. And although it has about 7 times as much as existing method's motion vector since each subband has different motion vector, it decreases motion compensated prediction error by detailed motion estimation, and then has better efficient coding performance. The experimental results with the proposed method showed about 0.3∼11.6% improvement of MAD performance in case of lossless coding, and 0.3∼3.0㏈ improvement of PSNR performance at the same bit rate in case of lossy coding.