• 한국지형공간정보학회:학술대회논문집
• /
• 1994.10a
• /
• pp.42-46
• /
• 1994

In this paper, we studied on an efficient detection and removal of the periodic scanner interference noise in LANDSAT images. Firstly, noise models and their characteristics are discussed. And we proposed a new scheme of noise detection in Fourier domain. Then, an dfficient noise filter can be designed based on the detected noise components. To verifythe effectiveness of our scheme, some experiments guided by our proposed scheme are performed using a real LANDSAT image.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2012.11a
• /
• pp.105-107
• /
• 2012

본 논문에서는 영상의 잡음제거에 주로 적용되어 왔던 양방향 필터(bilateral filter) 기법을 개량하여 에지 정보를 더 잘 살리게 하는 방법을 제안한다. 우선, 잡음 영상에서 에지의 위치를 파악하기 위한 방법으로, 이웃픽셀값들의 분산을 이용하는 방법을 제안한다. 또한 에지와의 거리를 기반으로 필터의 계수를 조정하는 방법을 제시한다. 따라서 제안하는 알고리즘을 적용하여 잡음 제거를 수행하면 기존의 잡음 제거율을 유지하면서도 에지정보를 보존한 결과를 얻을 수 있다.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.49 no.4
• /
• pp.23-30
• /
• 2012

This paper proposes an improved steganalysis method to detect the existence of secret message. Firstly, we magnify the small stego noise by multiplying the speckle noise to a given image and then we estimate the denoised image by using the soft thresholding method. Because the noises are not perfectly eliminated, some noises exist in the estimated cover image. If the given image is the cover image, then the remained noise will be very small, but if it is the stego image, the remained noise will be relatively large. The parent-child relationship in the wavelet domain will be slighty broken in the stego image. From this characteristic, we extract the joint statistical moments from the difference image between the given image and the denoised image. Additionally, four statistical moments are extracted from the denoised image for the proposed steganalysis method. All extracted features are used as the input of MLP(multilayer perceptron) classifier. Experimental results show that the proposed scheme outperforms previous methods in terms of detection rates and accuracy.

• Proceedings of the IEEK Conference
• /
• 2001.09a
• /
• pp.561-564
• /
• 2001

잡음에 의해 훼손된 영상 신호를 복원할 때 쓰이는 Wiener filter는 국부영역의 잡음 분산과 신호 분산을 가지고 적응적으로 필터의 파라미터를 조절한다. 그러나 기존의 Wiener filter는 고정된 필터 마스크를 사용함으로써, 평탄 영역의 잡음을 크게 제거하면, 에지 부분의 잡음이 살고, 에지 부분의 잡음을 제거하면, 평탄영역의 잡음이 사는 특성이 있다. 본 논문은 Kirsh mask로 에지와 그 방향성을 판별한 후, 에지 부분의 잡음을 제거하면서 평탄 영역의 잡음도 동시에 제거하기 위해 가변적인 필터 마스크를 사용했으며, 잡음에 의해 훼손된 방향성 정보를 살러 주기위해 필터 마tm크와 훼손된 영상 이미지에 방향성 정보를 추가했다. 제안된 방법으로 실험한 결과 주관적 비교에서 에피 부분이 잡음을 제거하고 방향성을 살렸으며, PSNR을 이용한 객관적 비교에서도 기존알고리즘보다 개선된 성능을 보였다.

• Journal of IKEEE
• /
• v.23 no.3
• /
• pp.910-916
• /
• 2019

Non-local similarity of natural images is one of highly exploited features in various applications dealing with images. Unique edges, texture, and pattern of the images are frequently repeated over the entire image. Once the similar image blocks are classified into a cluster, representative features of the image blocks can be extracted from the cluster. The bigger the size of the cluster is the better the additive white noise can be separated. Denoising is one of major research topics in the image processing field suppressing the additive noise. In this paper, a denoising algorithm is proposed which first clusters the noisy image blocks based on similarity, extracts the feature of the cluster, and finally recovers the original image. Performance experiments with several images under various noise strengths show that the proposed algorithm recovers the details of the image such as edges, texture, and patterns while outperforming the previous methods in terms of PSNR in removing the additive Gaussian noise.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2019.11a
• /
• pp.184-187
• /
• 2019

본 논문에서는 영상에서 발생하는 주기적 잡음을 제거하기 위해 다양한 필터들을 이용하여 성능 비교 실험을 수행한다. 영상의 주파수 도메인에서 지역적으로 잡음이 발생하면 영상의 공간 도메인에서 주기적인 잡음이 발생한다. 우선, 영상을 주파수 도메인에서 잡음을 야기시키는 영역을 분석하여 해당 영역에 지역적으로 노치 필터를 적용한다. 이를 통해 영상의 원신호를 유지하면서 영상에서 발생했던 주기적 잡음을 제거함으로써 영상의 화질이 개선됨을 실험을 통해 검증했다. 또한 객관적 지표 비교를 통해 3 가지의 지역적인 노치 필터들의 성능을 비교하고 최적의 필터를 제시한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.253-255
• /
• 2022

Thanks to the 4th industrial revolution and the development of various communication media, technologies such as artificial intelligence and automation are being grafted into industrial sites in various fields, and accordingly, the importance of data processing is increasing. Image noise removal is a pre-processing process for image processing, and is mainly used in fields requiring high-level image processing technology. Various studies have been conducted to remove noise, but various problems arise in the process of noise removal, such as image detail preservation, texture restoration, and noise removal in a special area. In this paper, we propose a switching mask filter based on the noise intensity to preserve the detailed image information during the impulse noise removal process. The proposed filter algorithm obtains the final output by switching to the extended mask when it is determined that the density is higher than the reference value when noise is determined in the area designated as the filtering mask. Simulation was conducted to evaluate the performance of the proposed algorithm, and the performance was analyzed compared to the existing method.

• Journal of the Institute of Convergence Signal Processing
• /
• v.20 no.3
• /
• pp.165-170
• /
• 2019

Recently, modern society has come up with the importance of video processing as various imaging systems have developed. However, deterioration occurs in the process of transmitting, processing, and storing video data for various reasons. Deterioration will damage the original image, and the typical noise is Salt and Pepper noise. There are A-TMF, CWMF, and linear interpolation as the means to eliminate Salt and Pepper noise. However, these methods show somewhat poor noise abatement performance in high-density noise areas. Therefore, this paper proposes an algorithm to eliminate noise using modified linear interpolation. To prove the validity of the proposed algorithm, PSNR, Profile was used to compare it with existing methods.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.8C
• /
• pp.788-794
• /
• 2003

It is very important to construct statistical model in order to exactly estimate the signal variance from the noisy image. By using estimated variance of original image, in general, Wiener filter is constructed, and it is applied to the noisy image. In this paper, we propose a new statistical mixture modeling of wavelet coefficients for image denoising. Firstly, a simple classification method is used to construct a significance map that captures significant property of wavelet coefficients. Based upon the significance map, the state probabilities of mixture model is computed, and signal variance is estimated by using them. Experimental results show that the proposed method yields 0.1-0.2㏈ higher PSNR than conventional methods for image denoising.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2003.06a
• /
• pp.14-17
• /
• 2003

웨이블릿 변환 영역에서 잡음제거 방법 중 Visushrink 추정에 사용되는 경계값은 측정 데이터 수와 잡음편차에 비례하는 것으로 알려져 있으나 잡음편차가 알려지지 않은 경우 Donoho는 웨이블릿 변환 영역의 최고대역에서 잡음편차 추정 방법을 제시하였다. 본 논문에서는 분산이 데이터 수에 반비례함을 이용하여 threshold 기법을 이용하여 잡음제거 시 계산량을 감소를 목적으로 차 신호를 이용하여 측정데이터 수를 줄인 후 영상신호의 가우시안 잡음을 soft threshold 기법을 적용하고 이 기법의 실용성을 밝혔다.