• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.447-450
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• 2010

하모닉 초음파 영상은 일반 초음파 영상에 비해 조직 간의 영상 대조도와 해상도를 향상 시키고, 경계가 보다 명확하기 때문에 초음파 영상 진단 분야에서 각광받고 있다. 하지만 초음파 영상이 포함하고 있는 스펙클 잡음 (speckle noise)에 의한 화질 저하는 하모닉 초음파 영상에서도 여전히 문제가 되고 있다. 이러한 스펙클 잡음을 제거하기 위해 많은 스펙클 제거 (despeckling) 방법들이 연구되었으며, 대부분의 방법들이 영상의 시각적 개선에 초점을 두고 있다. 이러한 접근 방법은 잡음개선정도와 영상의 정보 손실의 상반 관계 (trade off)를 갖는다. 한편 병변 분할은 이런 잡음 제거 방법에 따라 다른 분할 성능을 보이게 된다. 따라서 정확한 병변 분할을 위해서는, 스펙클 제거 방법에 따른 병변 분할 성능을 비교하고, 그 결과를 토대로 병변 분할에 효과적인 스펙클 제거 방법에 대한 연구가 필요하다. 본 논문에서는 유방 하모닉 초음파 영상에서 다양한 스펙클 제거 방법을 사용하여 각각의 필터가 병변 분할 성능에 미치는 영향을 비교해 보았으며, 실험 결과를 바탕으로 유방 병변 분할에 효과적인 전처리 역할을 수행하는 필터에 대해 분석해 보았다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1998.11a
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• pp.214-218
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• 1998

칼라 영상은 단색조의 영상에 비해 인간의 시각을 크게 향상시킨다. 따라서 칼라 영상 처리에 관한 연구는 매우 중요하다. 칼라 영상은 센서 잡음이나 채널 전송 에러에 의해 생기는 잡음에 의해 자주 오염되어진다. 이러한 칼라 잡음을 제거하기 위해 여러 형태의 필터들이 개발되어 왔는데 혼합된 잡음에서 벡터 $\alpha$-trimmed 평균 필터는 우수한 성능을 보였다. 그러나, 벡터 $\alpha$-trimmed 평균 필터는 필터링 과정이 영상의 전 영역에 걸쳐 균일하게 적용되어지기 때문에 윤곽선 이동이 일어나 blurring 현상이 심하게 나타나는 문제점이 있다. 이러한 문제점을 개선하기 위해 본 논문에서는 윤곽선 영역과 smooth 영역을 구분한 뒤 각 영역에 적합한 선택적인 필터링을 하는 조건적인 퍼지 클러스터 필터를 제안하였고 제안된 조건적인 퍼지 클러스터 필터는 기존의 벡터 $\alpha$-trimmed 평균 필터에 비해 혼합된 잡음에서 우수한 성능을 보였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1773-1778
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• 2012

Nowadays, the high quality of image is required with the demand for digital image processing devices is rapidly increasing. But image always damaged by many kinds of noises and it is necessary to remove noise and the denoising becomes one of the most important fields. In many cases image is corrupted by AWGN(additive white Gaussian noise). In this paper, we proposed an improved denoising algorithm with edge preservation. The proposed algorithm averages values processed by spatial weighted filter and self adaptive weighted filter. Then we add the value which is computed by the equation considering variance of mask and the estimated noise variance. Through the experience, the proposed filter performs well on noise suppression and edge preservation properties and improves the image visual quality.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.268-270
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• 2013

According to the development and supply of Wibro technology digital technology is applied in several fields. Digital images are damaged by various noises in the process of transfer and storage; the image restoration is to reduce the influence of the noises on images by removing the noises. To make good image restoration several methods have been proposed but the noise removal property is not satisfactory. Therefore, to effectively remove noises noise decision is made and if it is decided as a noise, the size of mask is enlarged; this is adaptive median filter algorithm that is proposed in this paper. And through simulation the superiority of this algorithm to existing methods has been verified.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.798-800
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• 2014

In recent years, according to the improvement of Digital image technology have been recently developed most of communication technology from multimedia communication service as well as image data transmission. But In the process of storing and transmitting noise is still generated in noise and the image degrades rapidly quality of a lot of image impulse noise. To eliminate this noise, SMF, CWMF, SWMF etc. The filters have been proposed to interfere with the noise characteristics of the filter are somewhat sufficient. Therefore, in this paper, in order to remove impulse noise is proposed a modified median filter. And impulse noise removal algorithms to confirm the existed PSNR(peak signal to noise ratio) from using conventional methods were compared.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.795-797
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• 2014

Image treatment has grown in its necessity in many fields due to the development of display technology used in smart phones and tablet computers. In digital imaging technology, noise is created by many causes during the process of acquiring, transmitting and treating image data. Therefore, this paper suggests a median filter that is more competent in removing noise by taking into account the direction when restoring noisy images that have been damaged by impulse noise. In order to verify the noise removal characteristics, PSNR(peak signal to noise ratio) was used for comparison against existing methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.953-955
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• 2016

Degradation is occurred in the process of the signal transmission in the image processing system due to various reasons. Degradation is noise addition in the image signal and the representative one to cause degradation is salt and pepper noise. Therefore, image restoring filter was suggested in this article to apply and process weighted value by the changes of each directional pixel upon breakdown of local mask with 8 directions in order to restore the damaged image in the environment of salt and pepper noise. In addition, peak signal to noise ratio (PSNR) was used to compare the existing method as the objective determinant standard of the improvement effect.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.133-135
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• 2022

With the development of IoT and AI technologies and media, various digital devices are being used, and unmanned and automation is progressing rapidly. In particular, high-level image processing technology is required in fields such as smart factories, autonomous driving technology, and intelligent CCTV. However, noise present in the image affects processes such as edge detection and object recognition, and causes deterioration of system accuracy and reliability. In this paper, we propose a filtering algorithm using fuzzy weights to reconstruct images damaged by complex noise. The proposed algorithm obtains a reference value using noise judgment and calculates the final output by applying a fuzzy weight. Simulation was conducted to verify the performance of the proposed algorithm, and the result image was compared with the existing filter algorithm and evaluated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1886-1891
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• 2017

Denoising which is one of major research topics in the image processing deals with recovering the noisy images. Natural images are well known not only for their local but also nonlocal similarity. Patterns of unique edges and texture which are crucial for understanding the image are repeated over the nonlocal region. In this paper, a nonlocal similarity based denoising algorithm is proposed. First for every blocks of the noisy image, nonlocal similar blocks are gathered to construct a overcomplete data set which are inherently sparse in the transform domain due to the characteristics of the images. Then, the sparse transform coefficients are filtered to suppress the non-sparse additive noise. Finally, the image is recovered by aggregating the overcomplete estimates of each pixel. Performance experiments with several images show that the proposed algorithm outperforms the conventional methods in removing the additive Gaussian noise effectively while preserving the image details.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.115-117
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• 2021

Currently, as IoT technology develops, monitoring systems are being used in various fields, and image processing is being used in various forms. Image data causes noise due to various causes during the transmission and reception process, and if it is not removed, loss of image information or error propagation occurs. Therefore, denoising images is essential. Typical methods of eliminating Salt and Pepper noise in images include AF, MF, and A-TMF. However, existing methods have the disadvantage of being somewhat inadequate in high-density noise. Therefore, in this paper, we propose an algorithm for determining noise for Salt and Pepper denoising and replacing the central pixel with an original pixel if it is non-noise, and processing the filtering mask by segmenting and averaging it in eight directions. We evaluate the performance by comparing and analyzing the proposed algorithms with existing methods.