• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.217-223
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• 2010

In the case of image magnification by using interpolation methods, interpolated pixels are estimated from the known pixels in source image. The magnified image is composed of the known pixels in source image and the interpolated pixels which is estimated. If the interpolated pixels are estimated to have the locality which is exists in real images, the magnified image is much closer to the real image. In this paper, an improved interpolation scheme is proposed to estimate pixels from the known pixels in source image using the locality which is exists in real images. The magnified image by using the proposed interpolation scheme is much closer to the real image. The performance of the proposed interpolation scheme is evaluated by using PSNR(Peak Signal to Noise Ratio) in experiment. The PSNR of the magnified image by using the proposed scheme is improved than that of the magnified images by using existing interpolation methods. So, the proposed interpolation scheme is an efficient interpolation method for the quality improvement of magnified image.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.63-73
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• 2015

In this paper, a quality improvement scheme is proposed for magnified image using the various curved surface characteristics of image. After testing horizontal and vertical directional surface characteristics of source image, interpolation value is calculated to have the surface characteristics such as simple convex surface, simple concave surface, and compound surface. The calculated interpolation value become the value of the interpolated pixel of magnified image. The calculated interpolation value is closer to the pixel value of real image. So, the quality of the magnified image is improved. The PSNR value of the magnified image using the proposed scheme is larger than the PSNR values of the magnified image using the existing techniques.

• Journal of the Korea Society of Computer and Information
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• v.18 no.2
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• pp.49-57
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• 2013

To improve the quality of magnified image, two schemes were proposed. The one is used to estimate simple convex surface and simple concave surface using the information of adjacent pixel values, and the other scheme is used to produce magnified image using the characteristics of simple convex surface and simple concave surface. The magnified image using the proposed scheme is more similar to real image than the magnified image using the previous schemes. The PSNR values of the magnified images using the proposed scheme are greater than those of the magnified images using the previous interpolation schemes.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.4
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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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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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.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3165-3168
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• 1999

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.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.95-102
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• 2011

Interpolation schemes are used widely in image magnification. Magnified image generated by interpolation scheme is composed of the known pixels in input image and the interpolated pixels estimated from the known pixels in input image. So, as the interpolated pixels are estimated to have locality which exists in real images, the magnified image is much closer to the real image. In this paper, an efficient interpolation scheme was proposed to provide locality for the interpolated pixels by using the characteristics of adjacent pixels in input image. The quality of magnified image using the proposed scheme was improved. In experiment, PSNR(Peak Signal to Noise Ratio) was used to evaluate the performance of the proposed scheme. The PSNR's of the magnified images generated by the proposed scheme were greater than those of the magnified images generated by the previous interpolation methods.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.59-68
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• 2013

In this paper, an effective scheme was proposed to estimate simple convex surface and simple concave surface which exist in image. This scheme is applied to input image to estimate simple convex surface or simple concave surface. When simple convex surface or simple concave surface exists, another proposed efficient interpolation scheme is used for the interpolated pixel to have the characteristics of simple convex surface or simple concave surface. The magnified image using the proposed schemes is more similar to the real image than the magnified image using the previous schemes. The PSNR values of the magnified images using the proposed schemes are greater than those of the magnified images using the previous interpolation schemes.

• Journal of the Korea Society of Computer and Information
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• v.19 no.8
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• pp.45-54
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• 2014

In this paper, we proposed an effective quality improvement scheme of magnified image using the surface characteristics in image. If the surface in image is estimated as simple convex surface or simple concave surface, the interpolated value can be calculated to have the surface characteristics by using the other method in the proposed scheme. The calculated value becomes the interpolated pixel value inmagnified image. So, themagnified image reflects the surface characteristics of the real image. If the surface is not estimated as simple convex surface or simple concave surface, the interpolated value is calculated more accurately than bilinear interpolation by using the method of the proposed scheme. The PSNR values of the magnified images using the proposed schemes are greater than those of the magnified images using the previous interpolation schemes.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.23-28
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• 2011

Ultrasound images for the abdominal muscles are complicated enough to have difficulty in interpreting their results. For better interpretation, magnifying the original image is necessary but its magnified image could be deteriorated and suffer from information loss. Thus, in this paper, we propose a magnifying method that reduces the gap between the original image and the magnified one in quality using a fuzzy method with weights for its brightness and interpolation. The proposed method extracts information of pixels in magnified image that have most similar characteristics of the original one by applying fuzzy membership function. In the process, the difference in the brightness between pixels of the magnified image and the original one using bilinear interpolation method and the weight value using the interpolation from multiplied values of four pixels are supplied to the fuzzy membership function. In this experiment, the proposed method reduces the cloudy phenomenon appears commonly compared to the bilinear interpolation method among those qualitative issues of image interpretation.