• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(C)
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• pp.188-190
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• 2011

Image interpolation is a technique that pervades many an application. Interpolation is almost never the goal in itself, yet it affects both the desired results and the ways to obtain them. In this paper, we proposed a technique that is capable to find out the error when the common two methods (bilinear and nearest neighbor interpolation) are applied on an image for rotation. The proposed technique also includes the comparison results of bilinear interpolation and nearest neighbor interpolation. Among them nearest neighbor interpolation gives us a better result regarding to the enhancement and due to least error. The error is found by using Mean Square Error (MSE).

• 한국인쇄학회지
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• 제16권3호
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• pp.81-95
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• 1998

If a image doesn't include sufficient data of output size and resolution, we will scan again the image. Interpolation generates a new pixel by methematical average of processing. In the interpolation method, there are nearest neighbor interpolation, bilinear interpolation and bicubic interpolation etc. This study was carried out for the purpose of researching compatible method to digital scan image caused by only different interpolation methods. Nearest neighbor interpolation show superior effect in the drawing image. Bilinear interpolation show reduction in detail and contrast. Bicubic interpolation show superior effect in the digital photo image USM(Unsharp Mask) application after extension by interpolation show better than extension by interpolation after USM(unsharp mask) application.

• 한국측량학회지
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• 제23권1호
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• pp.39-47
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• 2005

본 연구에서는 오늘날 해상측량에서 주로 사용되고 있는 DGPS기법과 음향측심기를 조합하여 취득된 해저지형의 3차원 위치정보를 크리깅(kriging), RBF(radial basis function), 최근린(nearest neighbor) 보간법을 이용하여, 항만공사에서의 호퍼준설량을 산정하였다. 또한, 각각의 보간법에 의해 산정된 호퍼준설량과 실제 준설량을 비교·분석함으로써, 준설량 산정에 있어 DGPS/Echo Sounder 기법의 활용성을 확인할 수 있었다. 그 결과, 크리깅 보간법을 적용한 경우 내용적 차이는 15,364㎥로 약 1.89%의 오차율을 나타내었으며, RBF 보간법과 최근린 보간법을 적용한 경우에는 각각 3.9%, 4.4%의 오차율을 나타내었다. 향후, 항만공사에서의 준설량 산정에 있어서 해저지형의 특성에 따른 적합한 보간법 적용에 관련한 연구가 선행될 경우, 보다 신속하고 정확한 준설량을 산정 할 수 있을 것으로 기대된다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2005년도 춘계학술대회 논문집
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• pp.115-124
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• 2005

This paper analyzes the problems that occurred in the magnification process for a fine input image and investigates a method to improve the problems. This paper applies a curve interpolation algorithm in CAD/CAM for the same test images with the existing image algorithm in order to improve the problems. As a result. the nearest neighbor interpolation. which is the most frequently applied algorithm for the existing image interpolation algorithm. shows that the identification of a magnified image is not possible. Therefore. this study examines an interpolation of gray-level data by applying a low-pass spatial filter and verifies that a bilinear interpolation presents a lack of property that accentuates the boundary of the image where the image is largely changed. The periodic B-spline interpolation algorithm used for curve interpolation in CAD/CAM can remove the blurring but shows a problem of obscuration, and the Ferguson's curve interpolation algorithm shows a more sharpened image than that of the periodic B-spline algorithm. For the future study, hereafter. this study will develop an interpolation algorithm that has an excel lent improvement for the boundary of the image and continuous and flexible property by using the NURBS. Ferguson's complex surface. and Bezier surface used in CAD/CAM engineering based on. the results of this study.

• 한국생산제조학회지
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• 제19권4호
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• pp.562-569
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• 2010

This paper analyzes the problems that occurred in the magnification process for a fine input image and investigates a method to improve the blurring of magnified image. This paper applies a curve interpolation algorithm in CAD/CAM for the same test images with the existing image algorithm in order to improve the blurring of magnified image. As a result, the nearest neighbor interpolation, which is the most frequently applied algorithm for the existing image interpolation algorithm, shows that the identification of a magnified image is not possible. Therefore, this study examines an interpolation of gray-level data by applying a low-pass spatial filter and verifies that a bilinear interpolation presents a lack of property that accentuates the boundary of the image where the image is largely changed. The periodic B-spline interpolation algorithm used for curve interpolation in CAD/CAM can remove the blurring but shows a problem of obscuration, and the Ferguson' curve interpolation algorithm shows a more sharpened image than that of the periodic B-spline algorithm. For the future study, hereafter, this study will develop an interpolation algorithm that has an excellent improvement for the boundary of the image and continuous and flexible property by using the NURBS, Ferguson' complex surface, and Bezier surface used in CAD/CAM engineering based on the results of this study.

• 감성과학
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• 제10권3호
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• pp.289-297
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• 2007

칼라 이미지 스케일은 칼라 전문가들의 지식에 의해 획득되고, 형용사와 대응되는 칼라(들)을 선택하기 위해 동일한 형용사 이미지 스케일들에서 형용사들과 칼라를 표현한다. 이들은 이미지 스케일을 얻기 위한 실험과 통계분석의 어려움 때문에 일반적으로, 단지 제한된 수의 칼라들만이 이미지 스케일에 위치한다. 이는 칼라를 선택하는 과정을 비전문가에게 어렵게 만든다. 본 논문에서는 이미지 스케일에 따라 연속적인 칼라를 제공하는 퍼지 K-근접 이웃 보간 방법에 기초를 둔 칼라 이미지 스케일의 보간 방법을 제안한다. 실험의 결과들은 보간된 이미지 스케일은 칼라 선택 과정에 있어 실용적으로 유용하게 사용될 수 있을 것이라 본다.

• 디지털산업정보학회논문지
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• 제16권1호
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• pp.55-65
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• 2020

With the development of display hardware, image interpolation techniques have been used in various fields such as image zooming and medical imaging. Traditional image interpolation methods, such as bi-linear interpolation, bi-cubic interpolation and edge direction-based interpolation, perform interpolation in the spatial domain. Recently, interpolation techniques in the discrete cosine transform or wavelet domain are also proposed. Using these various existing interpolation methods and machine learning, we propose decision tree classification-based image interpolation methods. In other words, this paper is about the method of adaptively applying various existing interpolation methods, not the interpolation method itself. To obtain the decision model, we used Weka's J48 library with the C4.5 decision tree algorithm. The proposed method first constructs attribute set and select classes that means interpolation methods for classification model. And after training, interpolation is performed using different interpolation methods according to attributes characteristics. Simulation results show that the proposed method yields reasonable performance.

• 디지털콘텐츠학회 논문지
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• 제15권6호
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• pp.737-743
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• 2014

단일 영상 초해상도 기법에는 보간 기반 방법과 표본 기반 방법 등이 있다. 보간 기반 방법들은 간결성에 강점을 가지고 있으나, 이들 방법들은 선지식을 이용할 수 없기 때문에 톱니 모양의 윤곽선을 가진 고해상도 영상을 생성하는 경향이 있다. 표본 기반 초해상도 기법에서는 최근방 기반 알고리즘들이 널리 이용되어 지고 있다. 그들 중, 네이버 임베딩은 지역적 선형 임베딩이라는 매니폴드 학습 방법의 개념과 같다. 그러나, 네이버 임베딩은 국부 학습 데이터 집합의 크기가 너무 작은데에 따른 빈약한 일반화 능력으로 인하여, 시각적으로나 정량적인 척도에 의해 취약한 성능을 보인다. 본 논문에서는 이와 같은 문제점을 해결하기 위해 개선된 네이버 임베딩 알고리즘을 제안하였다. 저해상도 입력 영상이 주어지면 고해상도 버전의 화소 값들은 개선된 네이버 임베딩 알고리즘에 의해 구해진다. 실험 결과 제안된 방법이 바이큐빅 보간법이나 네이버 임베딩에 비해 정량적인 척도 및 시각적으로도 우수한 결과를 보였다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 추계학술대회(한국공작기계학회)
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• pp.381-386
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• 2001

When a input image is extensively magnified on the computer system, it is almost impossible to replicate the original shape because of mismatched coordinates system. In order to resolve the problem, the shape of the magnified image has been reconfigured using the bilinear interpolation method, low pass special filtering interpolation method and B-spline interpolation method, Ferguson curve interpolation method based on the CAD/CAM curve interpolation algorithm. The computer simulation main result was that. Nearest neighbor interpolation method is simple in making the interpolation program but it is not capable to distinguish the original shape. Bilinear interpolation method has the merit to make the magnified shape smooth and soft but calculation time is longer than the other method. Low pass spatial filtering method and B-spline interpolation method has an effect to immerge the intense of the magnified shape but it is also difficult to distinguish the original shape. Ferguson curve interpolation method has sharping shape than B-spline interpolation method.

• 디지털산업정보학회논문지
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• 제16권3호
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• pp.49-58
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• 2020

Image interpolation, a technology that converts low resolution images into high resolution images, has been widely used in various image processing fields such as CCTV, web-cam, and medical imaging. This technique is based on the fact that the statistical distributions of the white Gaussian noise and the difference between the interpolated image and the original image is similar to each other. The proposed algorithm is composed of three steps. In first, the interpolated image is derived by random image interpolation. In second, we derive weighting functions that are used to apply non-local mean filtering. In the final step, the prediction error is corrected by performing non-local mean filtering by applying the selected weighting function. It can be considered as a post-processing algorithm to further reduce the prediction error after applying an arbitrary image interpolation algorithm. Simulation results show that the proposed method yields reasonable performance.