• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.331-333
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• 2003

KMA successfully began to receive and utilize the GOES-9 GVAR data since May 22nd 2003 when GOES-9 replaced the long-lived GMS-5 for Western Pacific and East Asian region until operation of MTSAT-1R in 2004. To take advantage of improvements of the GOES-9 data over the GMS-5 data, such as the increase of the temporal and spat ial resolution and addition of 3.9${\mu}$m channel, we have improved several algorithms to derive the meteorological products. Here we show two examples of algorithms, sea surface temperature and atmospheric motion vector, and preliminary results of validation of the improved algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1672-1686
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• 2013

In this paper, we propose a hybrid super-resolution algorithm robust to cut-change. Existing single-frame based super-resolution algorithms are usually fast, but quantity of information for interpolation is limited. Although the existing multi-frame based super-resolution algorithms generally robust to this problem, the performance of algorithm strongly depends on motions of input video. Furthemore at boundary of cut, applying of the algorithm is limited. In the proposed method, we detect a define boundary of cut using cut-detection algorithm. Then we adaptively apply a single-frame based super-resolution method to detected cut. Additionally, we propose algorithms of normalizing motion vector and analyzing pattern of edge to solve various problems of existing super-resolution algorithms. The experimental results show that the proposed algorithm has better performance than other conventional interpolation methods.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.3
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• pp.21-30
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• 1990

This paper describes a hardware implementation of the interframe monochrome video CODEC using a MC-CVQ(Motion Compensated and Classified Vector Quantization) algorithm. The specifications of this CODEC are (1) the resolution of image is $128{\times}128$ pixels, and (2) the transmission rates are about 10frames/sec at the 64Kbps channel. In order to design the CODEC under these conditions, it is implemented by a multiprocessor system composed of MC unit, CVQ nuit and decoder unit, which are controlled by microprogramming technique. And the 3~stage pipelined ALU(Arithmetic and Logic Unit) is adopted to calculate the minimum error distance in the MC unit and CVQ nuit. The realized system shows that the transmission rates are 6-15 frames/sec according to the relative motion of the video signal.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.17-24
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• 2004

In this paper, the wavelet video coding using Low-Band-Shift(LBS) method and multiresolution motion estimation(MRME) is proposed. To overcome shift- variant property on wavelet coefficients, the LBS was proposed. LBS method previously has superior performance in terms of rate-distortion characteristic. However, this method needs more memory and computational complexity. Therefore to reduce computational complexity of video coding using LBS, we combine MRME with LBS. When mm is applied only, it has 7 times as much as existing method's motion vector because each subband has different motion vector using property of LBS, number of motion vector decreases. Proposed method decreases motion vector, and it decreases motion compensated Prediction error by detailed motion estimation. And then it shows better coding performance. Also this method reduces computational amount by smaller search area in higher resolution. The computational complexity of the proposed method is 12.1% of that of existing method at 3-level wavelet transform. The experimental results with the proposed method show about 0.2∼9.7% improvement of MAD performance in case of lossless coding, and 0.1∼2.0㏈ improvement of PSNR performance at 4he same bit rate in case of lossy coding.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.188-191
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• 2002

To reduce the bit-rate of video sequences by removing temporal redundancy, motion estimation techniques have been developed. However, the high computational complexity of the problem makes such techniques very difficult to be applied to high-resolution applications in a real time environment. For this reason, low computational complexity motion estimation algorithms are viable solutions. If a priori knowledge about the motion of the current block is available before the motion estimation, a better starting point for the search of n optimal motion vector on be selected and also the computational complexity will be reduced. In this paper, we present an adaptive block matching algorithm based on temporal correlations of consecutive image frames that defines the search pattern and the location of initial starting point adaptively to reduce computational complexity. Experiments show that, comparing with DS(Diamond Search) algorithm, the proposed algorithm is about 0.1∼0.5(㏈) better than DS in terms of PSNR and improves as much as 50% in terms of the average number of search points per motion estimation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.2053-2061
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• 1997

The motion comensated video coding technology is very improtant to compress video signal since it reduces the temporal redundancies in successive frames. But the computational complexity of the motion estimation(ME) is too enormous to use in the area of real-time and/or resolution video processing applications. To reduce the complexity of ME, fast search algoritjms and hardware design methods are developed. Especially, the three step search(TSS) is well known method which shows stable performance in various video sequences. And other variations of TSS are developed to get better performance andto reduce the complexity. In this paepr, we present the modified TSS using neighboring block's motion vectors to determine first step motion vector in TSS. The presented method uses the correlation of the adjacent blocks with same motion field. The simualtion resutls show that it has a good MAE performance and low complexity comparing with original TSS.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.822-833
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• 1996

The video coding for very low bit rate has recently received considerable attention, but conventional block based transform coding schemes suffer from the blocking effect for the constraints of bit rates. In this paper, we present a video coding sysem suing multi-resolution motion estimation/compensation with variable size block(VMRME/C) and multi-resolution vector quantization(MRVQ) in wavelet transform domain for very low bit rate coding. It is shown that the presented scheme has better performance in the peak signal-to-nose ratio(RSNR) by 0.2-0.6 dB as well as subjective quality than that of conventional block based transform video coding techniques(especially, H. 263 which is DCT based video coding).

• ETRI Journal
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• v.31 no.6
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• pp.784-794
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• 2009

We present a full HD (1080p) H.264/AVC High Profile hardware encoder based on fast motion estimation (ME). Most processing cycles are occupied with ME and use external memory access to fetch samples, which degrades the performance of the encoder. A novel approach to fast ME which uses shared multibank memory can solve these problems. The proposed pixel subsampling ME algorithm is suitable for fast motion vector searches for high-quality resolution images. The proposed algorithm achieves an 87.5% reduction of computational complexity compared with the full search algorithm in the JM reference software, while sustaining the video quality without any conspicuous PSNR loss. The usage amount of shared multibank memory between the coarse ME and fine ME blocks is 93.6%, which saves external memory access cycles and speeds up ME. It is feasible to perform the algorithm at a 270 MHz clock speed for 30 frame/s real-time full HD encoding. Its total gate count is 872k, and internal SRAM size is 41.8 kB.

• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.345-354
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• 2005

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 a priori knowledge 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 presents the motion detection algorithm that can run robustly about recusive motion. The motion detection compares and analyzes two frames each other, motion of whether happened judge. Through experiments, we show significant improvements in the reduction of the computational time in terms of the number of search steps without much quality degradation in the predicted image.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.885-901
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• 2021

This paper illustratesthe impact of the temporal gap between satellite images and targetsize in mesoscale atmospheric motion vector (AMV) algorithm. A test has been performed using GEO-KOMPSAT-2A (GK2A) rapid-scan data sets with a temporal gap varying between 2 and 10 minutes and a targetsize between 8×8 and 40×40. Resultsshow the variation of the number of AMVs produced, mean AMV speed, and validation scores as a function of temporal gap and target size. As a results, it was confirmed that the change in the number of vectors and the normalized root-mean squared vector difference (NRMSVD) became more pronounced when smaller targets are used. In addition, it was advantageous to use shorter temporal gap and smaller target size for the AMV calculation in the lower layer, where the average speed is low and the spatio-temporal scale of atmospheric phenomena is small. The temporal gap and the targetsize are closely related to the spatial and temporalscale of the atmospheric circulation to be observed with AMVs. Thus, selecting the target size and temporal gap for an optimum calculation of AMVsrequires considering them. This paper recommendsthat the optimized configuration to be used operationally for the near-real time analysis of mesoscale meteorological phenomena is 4-min temporal gap and 16×16 pixel target size, respectively.