• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.105-114
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• 2006

In ubiquitous environment where various kinds of computers are embedded in persons, objects and environment and they are interconnected and can be used in my place as necessary, different types of data need to be exchanged between heterogeneous machines through home network. In the environment, the efficient processing, transmission and monitoring of image data are essential technologies. We need to make research not only on traditional image processing such as spatial and visual resolution, color expression and methods of measuring image quality but also on transmission rate on home network that has a limited bandwidth. The present study proposes a new motion vector estimation algorithm for transmitting, processing and controlling image data, which is the core part of contents in home network situation and, using algorithm, implements a real time monitoring system of multi dimensional images transmitted from multiple cameras. Image data of stereo cameras to be transmitted in different environment in angle, distance, etc. are preprocessed through reduction, magnification, shift or correction, and compressed and sent using the proposed metamorphosis hierarchical motion vector estimation algorithm for the correction of motion. The proposed algorithm adopts advantages and complements disadvantages of existing motion vector estimation algorithms such as whole range search, three stage search and hierarchical search, and estimates efficiently the motion of images with high variation of brightness using an atypical small size macro block. The proposed metamorphosis hierarchical motion vector estimation algorithm and implemented image systems can be utilized in various ways in ubiquitous environment.

• Journal of Korea Multimedia Society
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• v.21 no.9
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• pp.1052-1061
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• 2018

In this paper, we propose a new algorithm that is robust against the effects of objects that are relatively unaffected by camera motion and can accurately detect camera motion even in high resolution images. First, for more accurate camera motion detection, a global motion filter based on entropy of a motion vector is used to distinguish the background and the object. A block matching algorithm is used to find exact motion vectors. In addition, a matched filter with the angle of the ideal motion vector of each block is used. Motion vectors including 4 kinds of diagonal direction, zoom in, and zoom out are added additionally. The experiment shows that the precision, recall, and accuracy of camera motion detection compared to the recent results is improved by 12.5%, 8.6% and 9.5%, respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.237-247
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• 2003

The Motion Estimation (ME) process is an important part of a video encoding systems since they can significantly reduce bitrate with keeping the output quality of an encoded sequence. Unfortunately this process may dominate the encoding time using straightforward full search algorithm (FS). Up to now, many fast algorithms can reduce the computation complexity by limiting the number of searching locations. This is accomplished at the expense of less accuracy of motion estimation. In this paper, we introduce a new fast motion estimation method based on the spatio-temporal correlation of adjacent blocks. A reliable predicted motion vector (RPMV) is defined. The reliability of RPMV is shown on the basis of motion vectors achieved by FS. The scalar and the direction of RPMV are used in our proposed scheme. The experimental results show that the proposed method Is about l1~14% faster than the nearest neighbor method which is a wellknown conventional fast scheme.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.199-204
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• 2002

Since motion estimation and motion compensation methods remove the redundant data to employ the temporal redundancy in images, it plays an important role in digital video compression. Because of its high computational complexity, however, it is difficult to apply to high-resolution applications in real time environments. If we have information about the motion of an image block before the motion estimation, the location of a better starting point for the search of an exact motion vector can be determined to expedite the searching process. In this paper, we present an adaptive motion estimation approach bated on temporal correlations of consecutive image frames that defines the search pattern and determines the location of the initial search point adaptively. Through experiments, compared with DS(Diamond Search) algorithm, the proposed algorithm is about 0.1∼0.5(dB) better than DS in terms of PSNR(Peak Signal to Noise Ratio) and improves as high as 50% compared with DS in terms of average number of search point per motion vector estimation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.87-95
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• 2002

In this paper, we proposed a fast multi-resolution motion estimation(MRME) algorithm. This algorithm exploits the half-pixel accuracy motion estimation(HPAME) for exact motion vectors in the baseband and block classification for the reduction of bit amounts and computational loads. Generally, as the motion vector in the baseband are used as initial motion vector in the high frequency subbands, it has crucial effect on quality of the motion compensated image. For this reason, we exploit HPAME in the motion estimation for the baseband. But HPAME requires additional bit and computational loads so that we use block classification for the selective motion estimation in the high frequency subbands to compensate these problems. In result, we could reduce the bit rate and computational load at the similar image quality with conventional MRME. The superiority of the proposed algorithm was confirmed by the computer simulation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.56-65
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• 2009

Stereoscopic images consist of the left image and the right image. Thus, stereoscopic images have much amounts of data than single image. Then an efficient image compression technique is needed, the DPCM-based predicted coding compression technique is used in most video coding standards. Motion and disparity estimation are needed to realize the predicted coding compression technique. Their performing algorithm is block matching algorithm used in most video coding standards. Full search algorithm is a base algorithm of block matching algorithm which finds an optimal block to compare the base block with every other block in the search area. This algorithm presents the best efficiency for finding optimal blocks, but it has very large computational loads. In this paper, we have proposed fast disparity estimation algorithm using motion and disparity vector information of the prior frame in stereo image coding. We can realize fast disparity vector estimation in order to reduce search area by taking advantage of global disparity vector and to decrease computational loads by limiting search points using motion vectors and disparity vectors of prior frame. Experimental results show that the proposed algorithm has better performance in the simple image sequence than complex image sequence. We conclude that the fast disparity vector estimation is possible in simple image sequences by reducing computational complexities.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.167-170
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• 2000

In this paper, we present a fast algorithm for the motion estimation using the efficient selection of an initial search position. In the method, we select the initial search position using the motion vector from the subsmpled images, the predicted motion vector from the neighbor blocks, and the (0,0) motion vector. While searching the candidate blocks, we use the spiral search pattern with the successive elimination algorithm(SEA) and the partial distortion elimination(PDE). The experiment results show that the complexity of the proposed algorithm is about 2∼3 times faster than the three-step search(TSS) with the PSNR loss of just 0.05［dB］∼0.1［dB］ than the full search algorithm PSNR. The search complexity can be reduced with quite a few PSNR loss by controling the number of the depth in the spiral search pattern.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.10
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• pp.460-467
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• 2002

This paper proposes new motion vector re-estimation techniques for transcoding of heterogenous video coders. The first case is for transcoder of coding format. The coding algorithm with B-picture like MPEG standards is transcoded into the different algorithm without B-picture like H.261 standards. The second case is for transcoder of spatial resolution reduction. It generates a downscaled video bitstream at the video source. The third case is the integrated method that previous two cases are needed simultaneously. These three transcoding algorithms are compared and verified though reconstructed image quality in PSNR, motion vector errors between optimal motion vectors of cascaded trans- coder and motion vectors estimated by proposed methods and the amount of operation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.262-265
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• 2012

In this paper we propose a new deinterlacing method with block classification and motion vector smoothing. The proposed method classifies a block, then depending on the region it belongs to, the motion estimation or line averaging is applied. To classify a block its variance is calculated. Then, for those blocks that belong to simple non-texture region the line averaging is done while motion estimation is applied to complex region. The motion vector field is smoothed using median filter what yields more accurate interpolation. In the experiments for the subjective evaluation, the proposed method bas shown satisfying results in terms of computation time consumption and peak signal-to-noise ratio. Due to the simplicity of the algorithm computation time was drastically decreased.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1142-1149
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• 2004

Motion Estimation(ME) has been developed to reduce temporal redundancy in digital video signals and increase data compression ratio. ME is an Important part of video encoding systems, since it can significantly affect the output quality of encoded sequences. However, ME requires high computational complexity, it is difficult to apply to real time video transmission. for this reason, motion estimation algorithms with low computational complexity are viable solutions. In this paper, we present an efficient method with low computational complexity based on spatial and temporal correlations of motion vectors. The proposed method uses temporally and spatially correlated motion information, the motion vector of the block with the same coordinate in the reference frame and the motion vectors of neighboring blocks around the current block in the current frame, to decide the search pattern and the location of search starting point adaptively. Experiments show that the image quality improvement of the proposed method over MVFAST (Motion Vector Field Adaptive Search Technique) and PMVFAST (Predictive Motion Vector Field Adaptive Search Technique) is 0.01～0.3(dB) better and the speedup improvement is about 1.12～l.33 times faster which resulted from lower computational complexity.