• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1464-1468
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• 2004

The color conversion and color enhancement on gray image is presented in this paper. The pseudocoloring for RCB color components extraction from gray image is used the 2D U(Fast Wavelet Transform) for fille. bank and re-array. The each post processing is used the median filtering for noise reduction and the discrete color histogram equalization for CIT(Color Intensity Transformation). The experiment result has enhanced pseudocoloring image as PSNR 30dB over compared the processing of normal wavelet transform.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.4
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• pp.295-303
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• 2008

In general, transform domain adaptive filters show faster convergence speed than the time domain adaptive filters, but the amount of calculation increases dramatically as the filter order increases. This problem can be solved by making use of the subband structure in transform domain adaptive filters. In this paper, to increase the convergence speed on the generalized subband decomposition FIR adaptive filters, a structure of the adaptive filter with subfilter of dyadic sparsity factor in wavelet transform domain is designed. And, in this adaptive filter, the equivalent input in transform domain is derived and, by using the input, the convergence properties for the LMS algorithm is analyzed and evaluated. By using this sub band adaptive filter, the inverse system modeling and the periodic noise canceller were designed, and, by computer simulation, the convergence speeds of the systems on LMS algorithm were compared with that of the subband adaptive filter using DFT(discrete Fourier transform).

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.6
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• pp.82-90
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• 2011

This paper proposes an advanced outdoor localization algorithm of a GPS(global positioning system)-INS(inertial navigation system) integration system. In order to reduce noise from the internal INS sensors, discrete wavelet transform and variable threshold method are utilized. The UPF (unscented particle filter) combines GPS information and INS signals to implement precise outdoor localization algorithm and to reduce noise caused by the acceleration, deceleration, and unexpected slips. The conventional de-noising method is mainly carried out using a low pass filter and a high pass filter which essentially result in signal distortions. This newly proposed system utilizes the vibration information of actuator according to fluctuations of the velocity to minimize signal distortions. The UPF also resolves non-linearities of the actuator and non-normal distributions of noises. Effectiveness of the proposed algorithm has been verified through the real experiments and the results are demonstrated.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.309-316
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• 2014

In this paper, we propose an efficient detph map creation method using Graph Cut and Discrete Wavelet Transform. First, we have segmented the original image by using Graph Cut to process with its each areas. After that, the information which describes segmented areas of original image have been created by proposed labeling method for segmented areas. And then, we have created four subbands which contain the original image's frequency information. Finally, the depth map have been created by frequency map which made with HH, HL subbands and depth information calculation along the each segmented areas. The proposed method can perform efficient depth map creation process because of dynamic allocation using depth information. We also have tested the proposed method using PSNR(Peak Signal to Noise Ratio) method to evaluate ours.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1501-1514
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• 2008

The face shape extracted by the depth values has different appearance as the most important facial information. The face images decomposed into frequency subband are signified personal features in detail. In this paper, we develop a method for recognizing the range face images by multiple frequency domains for each depth image using the modified fuzzy c-mean algorithm. For the proposed approach, the first step tries to find the nose tip that has a protrusion shape on the face from the extracted face area. And the second step takes into consideration of the orientated frontal posture to normalize. Multiple contour line areas which have a different shape for each person are extracted by the depth threshold values from the reference point, nose tip. And then, the frequency component extracted from the wavelet subband can be adopted as feature information for the authentication problems. The third step of approach concerns the application of eigenface to reduce the dimension. And the linear discriminant analysis (LDA) method to improve the classification ability between the similar features is adapted. In the last step, the individual classifiers using the modified fuzzy c-mean method based on the K-NN to initialize the membership degree is explained for extracted coefficient at each resolution level. In the experimental results, using the depth threshold value 60 (DT60) showed the highest recognition rate among the extracted regions, and the proposed classification method achieved 98.3% recognition rate, incase of fuzzy cluster.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.4
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• pp.727-732
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• 2012

This paper presents an approach to classify normal and arrhythmia from the MIT-BIH Arrhythmia Database using Discrete Cosine Transform(DCT), Discrete Wavelet Transform(DWT) and neural network. In the first step, Discrete Cosine Transform is used to obtain the representative 15 coefficients for input features of neural network. In the second step, Discrete Wavelet Transform are used to extract maximum value, minimum value, mean value, variance, and standard deviation of detail coefficients. Neural network classifies normal and arrhythmia beats using 55 numbers of input features, and then the accuracy rate is 98.8%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.2
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• pp.257-266
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• 2007

In many multimedia applications, image compression is required to substantially reduce the amount of image data. This compression, however, sometimes brings artifacts. Typical artifacts are blocking artifacts and mosquito noise in DCT-coded images, and ringing artifacts around edges in wavelet-coded images. We propose a new directional postprocessing algorithm, which includes detection of the edge direction, interpolation scheme, and directional nonlinear filtering, to enhance the quality of decoded images. Simulation results show that the proposed algorithm is as effective as or more effective than other nonlinear filtering techniques.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.8B
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• pp.1119-1128
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• 2001

본 논문에서는 이차원(2-D) 이산 웨이블릿 면환(Discrete Wavelet Transform, DWT)을 이용한 연상압축기를 FPGA 칩에서 실시간으로 동작 가능하도록 하는 효율적인 메모리 스케줄링 방법(E$^2$M$^2$)을 제안하였다. S/W적으로 위의 메모리 사상 방법을 검증한 후, 실제로 상용화된 SFRAM을 선정하여 메모리 제어기를 구현하였다. 본 논문에서는 Mallet-tree를 이용한 2-D DWT 영상압축 칩을 구현할 경우를 가정하였다. 이 알고리즘은 연산 과정에서 많은 데이터를 정장하여야 하는데, FPGA는 많은 데이터를 저장할 수 있는 메모리가 내장되어 있지 않으므로 외부 메모리를 사용하여야 한다. 외부메모리는 열(row)에 대해서만 연속(burst) 읽기, 쓰기 동작이 가능하기 때문에 Mallet-tree 알고리즘의 데이터 입출력을 그대로 적용할 경우 실시간 동작을 수행하는 DWT 압축 칩을 구현할 수 없다. 본 논문에서는 데이터 쓰기를 수행할 경우에는 메모리 셀(cell)의 수직 방향을 저장시키고 읽기를 수행할 때는 수평으로 데이터의 연속 읽기를 수행함으로써 필터가 항상 수평 방향에 위치하게 하는 방법을 제안하였다. 입방법을 C-언어로 DWT 커넬(Kernel)과 메모리의 에뮬레이터(emulator)를 구현하여 실험한 결과, Mallat-tree 이론을 그대로 적용시켰을 때와 동일한 필터링을 수행할 수 있음을 검증하였다. 또한, 상용화된 SDRAM의 메모리 제어기를 H/W로 구현하여 시뮬레이션 함으로써 본 논문에서 제안한 방법이 실제적인 하드웨어로 실시간 동작을 할 수 있음을 보였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.413-416
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• 2005

Developement of computer and digitalizing of medical implement are being caused digitalizing of medical image. Medical Images are being managed more by PACS. In this situation comes out many problem about ownership, the right of properity of the medical images and notice wheather the data are modified. Digital watermarking can solve this problem. The proposed schemes have a two weak point that Non-blind method need a original image and Blind method use gaussian watermarking. In this paper, we propose a blind watermarking using binary image in order to easily recognize result of watermark This proposed scheme using wavelet transform and Circular Input method that input in medium-band of frequency domain.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.11a
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• pp.104-106
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• 2017

본 논문에서는 급부상하고 있는 가상현실 기술에서의 저작권 보호를 위해 VR영상을 타겟으로 하는 워터마킹 방법을 제안한다. 제안하는 방법은 VR영상의 합성에 널리 사용되는 SIFT 알고리즘을 통해 조건에 만족하는 점을 찾고, 그 점을 중심으로 한 주변 영역에 이산 웨이블릿 변환을 수행하여 워터마크를 삽입하는 방법이다. 또한 추출할 때에는 기존에 삽입한 워터마크와의 NCC값을 비교하여 일정 임계값 이상의 데이터들을 추출하고, 통계적 방법으로 최종 워터마크를 확정하게 된다. 이에 대해 가우시안 필터. 가우시안 노이즈, Sharpening, 회전변환, JPEG 압축 등의 공격을 가하고, 공격 후 추출되는 워터마크의 NCC, BER 값을 비교하여 워터마크의 강인성(robustness)을 확인한다.