• Journal of Korea Society of Industrial Information Systems
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• v.12 no.1
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• pp.39-45
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• 2007

In this paper, we present a new postprocessing algorithm using interpolation and signal adaptive filter according to the each block characteristic which is acquired in block classification process. We applied blocking artifact reduction algorithm for four neighbor low frequency block and ringing artifacts is removed with preserving edges by applying a signal adaptive filter in high frequency block based on edge map. The computer simulation results confirmed a better performance by the proposed method in both the subjective and objective image qualities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.121-123
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• 2021

Image processing is being used in various forms in important fields of the 4th industrial revolution, such as artificial intelligence, smart factories, and the IoT industry. In particular, in systems that require data processing such as object tracking, medical images, and object recognition, noise removal is used as a preprocessing step, but the existing algorithm has a drawback in that blurring occurs in the filtering process. Therefore, in this paper, we propose a filter algorithm using switching fuzzy weights. The proposed algorithm switches the fuzzy function by dividing the low-frequency region and the high-frequency region by the standard deviation of the filtering mask, and obtains the final output according to the fuzzy weight. The proposed algorithm showed improved results compared to the existing method, and showed excellent characteristics in the region where the high-frequency component is strong.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.82-83
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• 2019

본 논문에서는 휘도 및 색차 성분에 따른 SHVC 계층간 참조 픽처 생성 방법의 부호화 성능을 분석한다. SHVC 상위 계층에서는 하위 계층의 픽처를 DCT-IF 기반 업샘플링하여 사용한다. 상위 계층의 부호화 성능을 높이기 위해 딥러닝 기반 필터링을 이용하여 휘도, 색차 성분의 고주파 신호 복원이 부호화 성능에 미치는 영향을 분석한다. 기존 Y 성분에만 VDSR 네트워크를 이용하여 필터링을 적용하였을 때보다 색차 성분까지 필터링을 진행할 경우 최대 2.18%, 평균 1.5% 감소된 결과를 보였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.22-27
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• 2014

Blocking and ringing artifacts continue to be the most serious defects that occur in images and video streams compressed to low bit rates using block-based discrete cosine transform(DCT) compression standards. These artifacts contain the high frequency components near the block and the edge boundaries. Usually the lowpass filter can remove them. However, simple lowpass filter results into blur by removing important information such as edges at the same time. To overcome these problems, we propose a novel postfiltering algorithm that calculate the weight value based on the intensity similarity in the neighboring pixels and multiply this weight to the Gaussian lowpass filter coefficient. Experimental results show that the proposed technique provides satisfactory performance in both objective and subjective image quality.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.37-40
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• 2006

FM(Frequency Modulation) 음 합성방식은 오랫동안 연구되어 왔고 여러 가지 효과를 주기에 유용하고 비교적 낮은 사양으로 높은 수준의 배음을 합성할 수 있지만 그 응용분야가 대부분이 서양악기 위주의 연구였다. 이에 본 논문에서는 국악 관악기인 피리를 주파수 영역에서 저주파 영역과 고주파 영역으로 나누어 분석하고 이 결과를 이용하여 FM 파라미터를 추출하고 비대칭 FM합성방식으로 1차적인 소리를 합성하였다. 분석된 저주파 영역과 고주파 영역의 특성을 각각의 역 필터링을 위한 2개의 필터를 설계하여 이를 다시 합성된 소리를 통과시켜 두 소리를 합산함으로써 더욱 원음과 유사한 소리를 합성할 수 있었다.

• The Journal of the Acoustical Society of Korea
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• v.23 no.1
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• pp.54-60
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• 2004

In order to mitigate the problems in storage space and network bandwidth for the full CD quality audio, current digital audio is always restricted by sampling rate and bandwidth. This restriction normally results in low sample rate audio or calls for the data compression scheme such as MP3. However, they can only reproduce a lower frequency range than a regular CD quality because of the Nyquist sampling theory. Consequently they lose rich spatial information embedded in high frequency. The propose of this paper is to propose efficient high frequency enhancement of low sample rate audio using n adaptive filtering and DWT analysis and synthesis. The proposed algorithm uses the LMS adaptive algorithm to estimate the missing high frequency contents in DWT domain and it then reconstructs the spectrally enhanced audio by using the DWT synthesis procedure. Several experiments with real speech and audio are performed and compared with other algorithm. From the experimental results of spectrogram and sonic test, we confirm that the proposed algorithm outperforms the other algorithm and reasonably works well for the most of audio cases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1187-1193
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• 2014

This paper presents an effective motion estimation to improve the performance of the motion compensated temporal filtering (MCTF) which is a core part of the wavelet-based scalable video coding. The proposed scheme makes the motion vector field uniform by the modified median operation and the search strategies using adjacent motion vectors, in order to enhance the pixel connectivity which is significantly relevant to the performance of the MCTF. Moreover, the motion estimation with variable block sizes that reflects the features of frames is introduced for further correlation improvement of the motion vector field. Experimental results illustrate that the proposed method reduces the decomposed energy on the temporal high frequency subband frame up to 30.33% in terms of variance compared to the case of the full search with fixed block sizes.

• Journal of the Korean Society of Radiology
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• v.8 no.6
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• pp.301-307
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• 2014

In this study, an image acquired by the DSA(Digital Subtraction Angiography) system that is configured to configure the algorithm for high pass filtering algorithm experiments to improve the quality of angiography methods proposed. high pass filter is a high-frequency components pass through the filter, blocking low-frequency components. Part of the boundary line and contour of the organ corresponds to the high-frequency component is a high-frequency component of a medical image. Therefore, the high pass filter is also used for detection of the boundary line, but is also used for the high frequency enhancement. It was able to be analyzed by the proposed algorithm, to improve the quality of the angiography. Found out that the expression of the target site stand out clearly. The quality of the DSA system proposed in the wrong diagnosis software can be used to reduce, it is possible to develop and will further improve the accuracy of the treatment.

• 한국지구과학회:학술대회논문집
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• 2005.09a
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• pp.400-407
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• 2005

웨이브렛 변환(Wavelet Transform)은 시간영역과 주파수영역에서 동시에 분석이 가능하고 불연속적인 자료를 분석하는데 유리하기 때문에 그동안 영상을 처리하고 분석하는데 널리 이용되어 왔다. Discrete Wavelet Transform(DWT)는 주어진 영상에서 특성 정보는 유지하면서 다른 여러 종류의 계수로 분해 할 수 있게 해주기 때문에, 계수에 임계치를 적용해 고주파 성분을 제거하면 잡음을 줄일 수 있다. Stationary Wavelet Transform(SWT)는 DWT에서 다운샘플링에 의해 발생하는 문제점을 해결하기 위한 변환방법으로 잡음제거에 DWT보다 효과적이라고 알려져 있다. 이 연구에서는 DWT와 SWT에 의한 필터링을 광학영상과 레이더 영상에 적용하여 보고, 기존의 필터링 기법과 그 결과를 비교하였다. 그 결과 SWT에 의한 방법이 경계성분은 보존하면서 잡음을 가장 효과적으로 줄일 수 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.207-213
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• 2022

Recently, with the improvement of the performance of IoT technology and AI, automation and unmanned work are progressing in a wide range of fields, and interest in image processing, which is the basis of automation such as object recognition and object classification, is increasing. Image noise removal is an important process used as a preprocessing step in an image processing system, and various studies have been conducted. However, in most cases, it is difficult to preserve detailed information due to the smoothing effect in high-frequency components such as edges. In this paper, we propose an algorithm to restore damaged images in AWGN(additive white Gaussian noise) using fuzzy weights based on Gaussian distribution. The proposed algorithm switched the filtering process by comparing the filtering mask and the noise estimate with each other, and reconstructed the image by calculating the fuzzy weights according to the low-frequency and high-frequency components of the image.