• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2012.11a
• /
• pp.136-139
• /
• 2012

본 논문에서는 에지 검출기를 이용하여 선택적 디인터레이싱 방법을 제안한다. 제안하는 알고리즘은 LA 방법, M-ELA 방법 그리고 DOI 방법을 기본 방법으로 사용하였다. 제안한 방법에서 크게 3단계로 나눠진다. 먼저 비월주사 영상을 M-ELA 방법을 이용하여 에지의 방향을 예측한 후, 잃어버린 화소 값을 보간한다. 여기서 더 정밀한 에지를 검출하기 위해 소벨 연산을 사용하여 에지 방향에 따라 LA 방법, M-ELA 방법 그리고 DOI 방법을 선택적으로 보간하는 디인터레이싱 방법을 제안한다. 다양한 실험 영상에 대해 객관적 및 주관적 평가를 통해 제안한 알고리즘이 기존의 디인터레이싱 알고리즘보다 우수한 성능을 확인한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2011.11a
• /
• pp.331-332
• /
• 2011

본 논문에서는 Markov random field (MRF) 프레임워크와 영상의 기울기(gradient) 정보를 이용한 필드영상의 공간적 디인터레이싱(deinterlacing) 알고리즘을 제안한다. 기존의 디인터레이싱 결과를 보면 때때로 에지 부분의 연결이 정밀하지 못하여 눈에 거슬리는 재깅(jagging) 현상 등의 결함이 나타나기도 하는데, 제안하는 알고리즘은 이러한 현상을 줄이고자 영상의 기울기 도메인(gradient domain)에서 디인터레이싱을 수행한다. 즉, 제안하는 방식은 필드 영상으로부터 기울기 영상을 얻고 이를 보간한 후 필드영상과 복원된 기울기 영상을 토대로 원본 영상을 복원한다. 이 과정에서 각각의 픽셀마다 기울기 영상의 보간을 위한 에지 방향의 추정이 필요한데, 이 과정에서는 MRF 모델을 기반으로 에너지 함수를 설계하고 최적화시킴으로써 보다 강건한 추정결과를 얻도록 하였다. 프레임 영상 복원은 기울기 영상과 필드 영상 정보를 사전 정보로 하여 선형 방정식을 세우고 푸는 과정으로 이루어진다. 실험한 결과, 제안된 방법의 결과가 기존 방법에 비하여 눈에 띄는 결함을 줄이고 좋은 성능을 보임을 확인할 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.5C
• /
• pp.514-520
• /
• 2009

This paper proposes a new deinterlacing algorithm which improves the performance of the spatial filter. Extracting exact edges is very important element of deinterlacing performance. So the proposed algorithm has interpolated locally adaptive-thresholded binary image, and extracted exact edges from the interpolated binary image. The values of pixels on edges extracted from binary image are interpolated using neighborhood lines on the same edge. With computer simulations for a variety of images, it is shown that the proposed algorithm is much better than traditional methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2014.06a
• /
• pp.169-172
• /
• 2014

일반적으로 격행주사(interlace) 된 Side by Side (SbS) 영상의 경우 화면 재생 시, 전송 받은 영상을 먼저 디인터레이싱(de-interlacing) 한 후에 좌우 영상을 분리하여 수평 해상도를 보간 하는데, 이때 한번 가공된 디인터레이싱 값을 참조하여 보간 값을 결정하게 되는 관계로 수평 해상도의 정확성이 크게 떨어지게 된다. 이러한 문제점을 해결하기 위해 격행주사 방식의 SbS 3D 영상의 수평 해상도 보간 방법을 제안한다. 수평 해상도 보간 시에 격행주사 방식으로 전송 받은 라인과 디인터레이싱 기법을 이용해 보간한 라인의 특성에 따라 각 라인에서 활용할 수 있는 전송 받은 값을 가지고 각각 다른 보간 방법을 적용함으로써 정확도를 향상하는 방법을 제안한다. 제안된 방법의 실험 결과는 기존의 보간 기법들보다 주관적, 객관적 화질에서 더욱 우수한 성능을 보여준다.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.5
• /
• pp.87-97
• /
• 2004

In this paper, we propose an algorithm for interlaced-to-progressive conversion by the weighted summation of the information collected from spatial do-interlacing method, in which the weighted edge based line average is applied, and the temporal method in which the motion compensation is employed by using hi-directional BMA (block matching algorithm). We employed time-recursive and motion adaptive processing as motion detection is involved. Also, a median filter is used to deal with limitation of the linear summation in which only an intermediate of values being involved is determined. The main goal of the approach is to overcome the shortcomings of each of the do-interlacing techniques without significant increment of the computational complexity, and the proposed method is apt to implement in hardware for real-time processing.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.6
• /
• pp.68-77
• /
• 2009

A single field deinterlacing method, namely interpolation algorithm derived from low resolution (ILR), is presented in this paper. Traditional deinterlacing methods usually employ edge-based interpolation technique within pixel-based estimation. However, edge-based methods are somehow sensitive to noise and intensity variation in the image. Moreover, the methods are not satisfied in deciding the exact edge direction which controls the performance of the interpolation. In order to reduce the sensitivity, the proposed algorithm investigates low-resolution characteristics of the pixel to be interpolated, and applies it to high-resolution image. Simulation results demonstrates that the proposed method gives not only a better objective performance in terms of PSNR results compare to conventional edge-based interpolation methods, but also better subjective image quality.

• The Journal of the Convergence on Culture Technology
• /
• v.6 no.1
• /
• pp.449-454
• /
• 2020

We propose an improved de-interlacing method that converts the interlaced images into the progressive images by one field. In the first, Inter-pixel values are calculated by applying Newton's forward difference, backward difference interpolation from upper and lower 5 pixel values. Using inter-pixel values obtained from upper and lower 5 pixel values, it makes more accurate a direction estimate by applying the correlation between upper and lower pixel. If an edge direction is determined from the correlation, a missing pixel value is calculated into the average of upper and lower pixel obtained from predicted direction of edge. From simulation results, it is shown that the proposed method improves subjective image quality at edge region and objective image quality at 0.2~0.3dB as quantitative calculation result of PSNR, compared to previous various de-interlacing methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.9
• /
• pp.2209-2215
• /
• 2014

This paper presents, a deinterlacing method by improving the Direction-Oriented Interpolation (DOI) technique. The technique is considered to be a very strong tool for intrafield-based deinterlacing. However, DOI has some problems such as long processing time, wrong edge detection in periodic pattern. To remedy this problem, we replace the full search in DOI by a two-step search to reduce processing time and introduces two additional processes to improve image quality. In the proposed method, the spatial direction vectors (SDVs) misread data are reconsidered to prevent them utilizing in the next interpolation step, resulting in an accurate deinterlacing method. We conduct experiments with ISO experimental images to compare the proposed method with the existing methods including line evarage (LA), edge-based line averaging (ELA), DOI, selective deinterlacing algorithm (SDA). Experimental results show the proposed method gives better performance in objective and subjective quality than existing deinterlacing methods.

• Journal of Broadcast Engineering
• /
• v.19 no.6
• /
• pp.789-797
• /
• 2014

In general, the image of interlaced side-by-side (SBS) streams is not good because it goes through two reconstruction steps-de-interlacing and horizontal interpolation. Especially the accuracy of horizontal resolution is greatly deteriorated as processed de-interlacing value is used for reference of interpolated pixel at time of horizontal interpolation. To solve this problem, we propose an improved method considering interlaced SBS stream's characteristics. In this paper, we adopted two separate methods to transmitted line and blank line for using reliable information. The experimental result of the proposed method is better than the conventional algorithm in terms of subjective and objective image quality.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.10C
• /
• pp.1000-1009
• /
• 2007

This paper presents a content adaptive interpolation (CAI) for intra deinterlacing. The CAI consists of three steps: pre-processing, content classification, and adaptive interpolation. There are also three main interpolation methods in our proposed CAI, i.e. modified edge-based line averaging (M-ELA), gradient directed interpolation (GDI), and window matching method (WMM). Each proposed method shows different performances according to spatial local features. Therefore, we analyze the local region feature using the gradient detection and classify each missing pixel into four categories. And then, based on the classification result, a different do-interlacing algorithm is activated in order to obtain the best performance. Experimental results demonstrate that the CAI method performs better than previous techniques.