• Journal of the Institute of Convergence Signal Processing
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• v.9 no.4
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• pp.245-252
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• 2008

In this paper, we propose a new method for improving the H 264 encoding process and motion estimation part. Our approach is a method to reduce the encoding running time through the omission of reference frame in the mode selection process of H 264 and an improvement of SAD computing process. To evaluate the proposed method, we used the H 264 standard image of QCIF size and TIN 4:2:0 format. Experimental results show that proposed SAD algorithm 1 can improve the speed of encoding runnung time by an average of 4.7% with a negligible degradation of PSNR. However, SAD algorithm 2 can improve the speed of encoding runnung time by an average of 9.6% with 0.98dB degradation of PSNR.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.3
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• pp.405-417
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• 2001

In this paper, since we currently using surveillance system of analog type bring about waste of resource and efficiency deterioration problems, we describe new solution that design and implementation to the digital surveillance system of new type applying compression techniques and encoding techniques of image data using MPEG-2 international standard. Also, we proposed fast motion estimation algorithm requires much less than the convectional digital surveillance camera system. In this paper a fast motion estimation algorithm is proposed the MPEG-2 video encoding. This algorithm is based on a hybrid use of the block matching technique and gradient technique. Also, we describe a method of moving object extraction directly using MPEG-2 video data. Since proposed method is very simple and requires much less computational power than the conventional object detection methods. In this paper we don't use specific H/W and this system is possible only software encoding, decoding and transmission real-time for image data.

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.162-165
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• 2018

In this paper, we propose a pre-processing procedure to obtain scene change information using spatial down-scaled input image for efficient encoding of super-high resolution image and propose a reconstruction of reference picture list in inter-picture prediction using this information. The experimental results show that the proposed method improves the BD-Rate by 0.44% and reduces encoding time by 12.46% when compared to HM 16.12.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.1
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• pp.61-73
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• 2012

The paper presents the novel approach to solve some problems occurred in application of the genetic algorithm to the determination of the optimal tire pattern sequence in order to reduce the tire air-pumping noise which is generated by the repeated compression and expansion of the air cavity between tire pattern and road surface. The genetic algorithm has been used to find the optimal tire pattern sequence having a low level of tire air-pumping noise using the image based air-pumping model. In the genetic algorithm used in the previous researches, there are some problems in the encoding structure and the selection of objective function. The paper proposed single encoding element with five integers, divergent objective function based on evolutionary process and the optimal evolutionary rate based on Shannon entropy to solve the problems. The results of the proposed genetic algorithm with evolutionary process are compared with those of the randomized algorithm without evolutionary process on the two-dimensional normal distribution. It is confirmed that the genetic algorithm is more effective to reduce the peak value of the predicted tire air-pumping noise and the consistency and cohesion of the obtained simulation results are also improved in terms of probability.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.1
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• pp.124-131
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• 1997

There have been many demands for th ereal-time image compression. The image compression systems have a wide range of applications. However, real-time encoding is hard to implement because it needs a large amount of computations. In particular, the discrete cosine transform (DCT) and motion estimatio require a large number of arithmetic oeprations compared to other algorithms in MPEG-2. The conventional fasdt DCT algorithms have focused on the reduction of the number of additions more cycles and more expense in realization. Because TMS320C80 has special structure, new approach for implementation of DCT is suggested. The selection of adaptive algorithm and optimization is requried TMS320C80 are analyzed an dsome adaptive DCT algorithms are selected. The DCT algorithms are optimized and implemented. Chens and lees DCT algorithms among various fast algorithms are selected because 1-D approach is effective in the view of th einternal structure of TMS320C80. According to the simulation result, Lees algorithm is more effective in speed and has little difference in precision. On the basis of the result, the possibility of DCT implementation for real-time MPEG-2 system is verified and the required number of the processor, called advanced DSP, is decided for real-time MPEG-2 encoding and decoding.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.7A
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• pp.1063-1075
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• 2000

This paper proposes an adaptive error concealment technique for compressed video. Since redundancy is extracted out during compression process, compressed video is vulnerable to errors which occur during transmission of video over error prone networks such as wireless channels and Internet. Error concealment is a process of reconstructing video out of damaged video bit stream. We proved that scalable encoding is very useful for error concealment. Analysis of experiments shows that some part of image is better concealed by using base layer information and other part of image is better concealed by using previous frame information. We developed a technique which enables to decide which methodology is more effective, adaptively, based on motion vectors and regional spatial activity. We used H.263v2 for scalable encoding, but, our approach could be applied to all DCT based video codec.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.125-128
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• 2000

The conventional fractal decoding was required a vast amount computational complexity. Since every range blocks was implemented to IFS(iterated function system). In order to improve this, it has been suggested to that each range block was classified to iterated and non-iterated regions. If IFS region is contractive, then it can be performed a fast decoding. In this paper, a searched region of the domain in the encoding is limited to the range region that is similar with the domain block, and IFS region is a minimum. So, it can be performed a fast decoding by reducing the computational complexity for IFS in fractal image decoding.

• KSCI Review
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• v.2 no.1
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• pp.130-139
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• 1995

This paper suggests the method to shorten the search area by using edge detection and subimage partition. For the purpose reduce encoding time, The Domain areas are reduced 1/64 by partitioning original image to subimage, and classified them into edge area and shade area so that detect only the area in the same class. for achieving an encoding with good fidelity, tried to differ the search method as the threshold value of edge which is included in subimage, and compared the compression rate and fidelity when set the size of range block as $4{\times}4$ and $8{\times}8$.

• Investigative Magnetic Resonance Imaging
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• v.20 no.4
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• pp.215-223
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• 2016

Purpose: The management of metal-induced field inhomogeneities is one of the major concerns of distortion-free magnetic resonance images near metallic implants. The recently proposed method called "Slice Encoding for Metal Artifact Correction (SEMAC)" is an effective spin echo pulse sequence of magnetic resonance imaging (MRI) near metallic implants. However, as SEMAC uses the noisy resolved data elements, SEMAC images can have a major problem for improving the signal-to-noise ratio (SNR) without compromising the correction of metal artifacts. To address that issue, this paper presents a novel reconstruction technique for providing an improvement of the SNR in SEMAC images without sacrificing the correction of metal artifacts. Materials and Methods: Low-rank approximation in each coil image is first performed to suppress the noise in the slice direction, because the signal is highly correlated between SEMAC-encoded slices. Secondly, SEMAC images are reconstructed by the best linear unbiased estimator (BLUE), also known as Gauss-Markov or weighted least squares. Noise levels and correlation in the receiver channels are considered for the sake of SNR optimization. To this end, since distorted excitation profiles are sparse, $l_1$ minimization performs well in recovering the sparse distorted excitation profiles and the sparse modeling of our approach offers excellent correction of metal-induced distortions. Results: Three images reconstructed using SEMAC, SEMAC with the conventional two-step noise reduction, and the proposed image denoising for metal MRI exploiting sparsity and low rank approximation algorithm were compared. The proposed algorithm outperformed two methods and produced 119% SNR better than SEMAC and 89% SNR better than SEMAC with the conventional two-step noise reduction. Conclusion: We successfully demonstrated that the proposed, novel algorithm for SEMAC, if compared with conventional de-noising methods, substantially improves SNR and reduces artifacts.

• Journal of KIISE:Software and Applications
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• v.27 no.4
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• pp.432-440
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• 2000

In this study, a new algorithm for canceling MRI artifact due to translational motion in image plane is described. Unlike the conventional iterative phase retrieval algorithm, in which there is no guarantee for the convergence, a direct method for estimating the motion is presented. In previous approaches, the motions in the x(read out) direction and the y(phase encoding) direction are estimated simultaneously. However, the features of x and y directional motions are different from each other. By analyzing their features, each x and y directional motion is canceled by different algorithms in two steps. First, it is noticed that the x directional motion corresponds to a shift of the x directional spectrum of the MRI signal, and the non-zero area of the spectrum just corresponds to the projected area of the density function on the x-axis. So the motion is estimated by tracing the edges between non-zero area and zero area of the spectrum, and the x directional motion is canceled by shifting the spectrum in inverse direction. Next, the y directional motion is canceled by using a new constraint condition, with which the motion component and the true image component can be separated. This algorithm is shown to be effective by using a phantom image with simulated motion.