• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.676-678
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• 2016

Noise occurs in the process of obtaining, transmission, and processing in image processing systems and these noises lower the resolution of image and cause visual errors. Currently, a representative filter to remove salt and pepper noise is SMF(standard median filter) but it is inadequate in preserving edge as the noise field expands. Therefore, for salt and pepper noise enviroment, the study suggested and algorithm that are places with original pixel when the central pixel is non-noise and process by applying weighted value on areas with less local mask pixel changes when there is noise.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2004.11a
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• pp.71-74
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• 2004

본 논문에서는 MAP(maximum a posteriori) 추정방식과 국부통계특성을 이용한 적응적 영상 향상 방법을 제안한다. 원 영상의 에지를 보존 할 수 있는 MAP추정 방식과 인간의 시각 특성을 나타내는 시각 함수를 이용한 가중치 행렬을 사용하였다. MAP 추정 방식은 컨벡스 함수를 최적화하여 원 영상의 에지를 보존하는 방법을 이용하였으며, 시각 함수는 국부 정보의 평균, 분산을 이용하여 정의하였다. 제안 방식으로부터 국부영역의 비용함수에 의해 발생되는 스무딩 정도를 다르게 하여 보간된 영상의 화질을 개선시킨다. 제안된 방식의 성능을 실험 결과로부터 확인한 수 있었다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.87-87
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• 2001

일반화 대칭 변환 (generalized symmetry transform, GST)은 주어진 영상에서 사전 분할이 없이 국부성과 반사 대칭성을 결합하여 대칭을 측정하고 관심 영역을 추출한다. GST의 거리 가중치 함수에서 국부적인 대칭성이 반영되며 이 함수의 표준 편차 u에 의해 GST의 수행 범위가 조절된다. 넓은 관심영역을 추출하기 위해 반지름 r이 큰 검색영역 내에서의 대칭성이 추출될 필요가 있다. 이에 따라서 GST의 수행시간은 r에 따라 2차적으로 증가하게 된 본 논문에서는 이를 개선하기 위해 선택적 방향 주의를 가지는 수정된 스캔라인 GST를 제안한다. 제안된 GST는 기존의 GST와 유사한 대칭 특성을 추출하지만 선택적 방향의 기울기만을 고려한 스캔라인 위의 에지 화소쌍에서 GST를 수행함으로써 r에 따라서 이의 수행시간이 선형적으로 증가된다 특히 r이 큰 경우에 선택적 방향에 대해서만 적용하면 기존의 GST의 계산량이 비대해지는 단점을 보완해 줄 수 있다. 제안된 GST가 기존의 GST보다 시간적으로 효과적이며 유용하다는 것이 여러 종류의 영상에 대한 실험으로 확인되었다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.41-46
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• 2005

Deinterlacing is the conversion from interlaced to progressive scan image that is considered to be 2 times image interpolation. In this paper, the simple and effective deinterlacing method is proposed based on the local gradient information of neighborhood pixels. In the proposed method, the weights for directions around the pixel to be interpolated are estimated, and the weighted sum for the neighborhood pixels is the final intensity value of the pixel to be interpolated. The proposed method has the structure suitable to practical implementation and can avoid the artifacts due to the wrong detection of edge direction. In the simulation, it showed improved subjective and objective performance than the ELA method and comparable performance compared with the variation of ELA method which has more complex structure and requires a couple of parameters that is determined by experience.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.671-673
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• 2016

In image data, noise occurs due to various external factors in the process of obtaining and transmitting. There are various types of noise according to the cause and form and research to remove this noise is being continued. Therefore the study suggested a way to filter to restore images damaged by salt and pepper noise which preserves non-noise signal and processes noise signal by expanding mask size according to the local mask noise density. In addition, as an objective evaluation standard of improvements, the study used PSNR(peak signal to noise ratio) to compare with previous methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1194-1200
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• 2006

In this paper, we propose an adaptive MAP (Maximum A Posteriori) high-resolution image reconstruction algorithm using local statistics. In order to preserve the edge information of an original high-resolution image, a visibility function defined by local statistics of the low-resolution image is incorporated into MAP estimation process, so that the local smoothness is adaptively controlled. The weighted non-quadratic convex functional is defined to obtain the optimal solution that is as close as possible to the original high-resolution image. An iterative algorithm is utilized for obtaining the solution, and the smoothing parameter is updated at each iteration step from the partially reconstructed high-resolution image is required. Experimental results demonstrate the capability of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1477-1482
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• 2022

Haze is a local weather phenomenon in which very small droplets float in the atmosphere, and the amount and characteristics of haze may vary depending on the region. In particular, these haze reduce visibility, which can cause air traffic interference and vehicle traffic accidents, and degrade the quality of security CCTVs and so on. Therefore, in the past 10 years, research on haze removal has been actively conducted to reduce damage caused by haze. In this study, local haze removal is performed by weight generation using a haziness degree evaluator to adaptively respond to haze-free, homogeneous haze, and non-homogeneous haze cases. And the proposed method improves the limitations of the existing static haze removal method, which assumes that there is haze in the input image and removes the haze. We also demonstrate the superiority of the proposed method through quantitative and qualitative performance evaluations with benchmark algorithms.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.287-290
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• 2002

본 논문에서는 디지털 컨텐츠 저작권 보호를 위해 강인성과 비가시성의 유지를 위한 보다 효과적인 방법으로 웨이브릿 변환에서 적응적 워터마크 삽입강도를 갖는 지각적 데이터 은닉 모델을 제안한다. 먼저 영상을 9/7 쌍직교 웨이브릿 필터를 사용해 4레벨로 다해상도 분해한다. 다음으로 연속부대역 양자화(successive subband quantization)를 통한 시각적 중요계수(perceptually significant coefficient: PSC)들을 선정하여 선택된 계수들에 대해서만 워터마크 정보를 삽입한다. 지각 모델은 정상상태의 일반화 가우시안 모델(generalized gaussian model)로 추정된 NVF(noise visibility function)로 에지와 텍스쳐영역 그리고 평탄영역에 따라 각각 적응적으로 삽입되게 한다. 이는 각 서브밴드 내의 분산과 형상계수(shape parameter)에 의해 결정된다. 적응적 워터마크의 삽입강도를 갖기 위해 에지와 텍스쳐영역의 삽입강도는 각 서브밴드의 주파수 감도(frequency sensitivity)로 결정되고, 평탄영역의 삽입강도는 영상의 국부적 특성에 근거한 통계적 가중치를 사용한다. 삽입되는 워터마크는 랜덤시퀀스로 N(0,1)이다. 여러 가지 공격에 대한 실험으로 제안한 방법의 비가시성과 강인성을 확인한다.

• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.313-321
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• 2005

Digital halftoning is a process to produce a binary image so that the original image and its binary counterpart appear similar when observed from a distance. Among digital halftoning methods, error diffusion is a procedure for generating high quality bilevel images from continuous-tone images but blurs the edge information in the bilevel images. To solve this problem, we propose the improved error diffusion using local spatial information of the original images. Based on the fact that the human vision perceives not a pixel but local mean of input image, we compute edge enhancement information(EEI) by appling the ratio of a pixel and its adjacent pixels to local mean. The weights applied to local means is computed using the ratio of local activity measure(LAM) to the difference between input pixels of 3$\times$3 blocks and theirs mean. LAM is the measure of luminance changes in local regions and is obtained by adding the square of the difference between input pixels of 3$\times$3 blocks and theirs mean. We add the value to a input pixel of quantizer to enhance edge. The performance of the proposed method is compared with conventional methods by measuring the edge correlation. The halftone images by using the proposed method show better quality due to the enhanced edge. And the detailed edge is preserved in the halftone images by using the proposed method. Also the proposed method improves the quality of halftone images because unpleasant patterns for human visual system are reduced.

• Journal of KIISE:Software and Applications
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• v.37 no.8
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• pp.629-640
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• 2010

The exemplar-based inpainting model is widely used to remove objects from natural images and to restore a damaged region. This paper presents a method which improves the performance of the conventional exemplar-based inpainting model by modifying three major parts in the model: data term, confidence term and patch selection. While the conventional data term is calculated using the local gradient, the proposed method uses 16 compass masks to get the global gradient to make the method robust to noise. To overcome the problem that the confidence term gets negligible in the inside of the eliminated region, a method is proposed which makes the confidence term decrease slowly in the eliminated region. The patch selection procedure is modified so that the closer patch has higher weight. Experiments showed that the proposed method produced more natural images and lower reconstruction error than the conventional exemplar-based inpainting.