• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.456-456
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• 2000

The back projection histogram method has been proposed as the method to construct an image from waves reflected from a buried object for subsurface radar. This method is compose of two phases, i.e., a back projection image construction process and a back projection image superposition process. A simulation analysis of this method has been studied. In this paper, an experimental study is demonstrated in air as the homogeneous Held using three cylinders as buried objects.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.264-267
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• 2015

본 논문에서는 개선된 고속의 Back Projection 기법과 에지맵 보간을 이용한 단일영상 기반의 초해상도(super resolution) 영상을 생성하는 알고리즘을 제안한다. 본 논문에서 제안하는 알고리즘은 영상의 색채 왜곡을 방지하기 위해 RGB 컬러 도메인에서 HSV 컬러 도메인으로 변경하여 밝기정보인 V만 이용한다. 먼저 잡음제거와 속도 향상을 위해 개선된 고속 back projection을 이용해 영상을 확대 재구성한다. 이와 함께 LoG(laplacian of gaussian) 필터링을 이용하여 에지 맵을 추출한다. 에지의 정보와 back projection의 결과를 이용하여 고해상도 영상을 재구성한다. 제안하는 알고리즘을 이용하여 복원한 영상은 부자연스러운 인공물을 효과적으로 제거하고, blur현상을 줄여 에지 정보를 보정하고 강조해준다. 또한 실험을 통해 제안하는 알고리즘이 기존의 보간법과 전통적인 back projection 결과보다 주관적인 화질이 우수하고 객관적으로 우수한 성능을 나타내는 것을 입증한다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.11
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• pp.1054-1062
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• 2011

This study describes the time domain imaging algorithm which can be well applied to short-range UWB(ultra wideband) bistatic radar. In the imaging method of SAR technology, the frequency domain method is well applied to the areas which satisfy far-field condition. However in the near-field environment, the image quality is not good due to phase error. However back-projection method based on time domain is well applied to short-range imaging radar. Meanwhile because its processing time is very long, real time-processing is very difficult. To resolve this problem FFBP(Fast Factorized Back-Projection) was proposed. Using the raw data gathered on field we implemented back-projection and FFBP method. Then image quality and processing time were analyzed using these methods.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.715-717
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• 2004

This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on a recursive error back-projection of top-down machine learning. A face is represented by a linear combination of prototypes of shape and texture. With the shape and texture information about the pixels in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those of texture by solving least square minimization. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes, In addition to, a recursive error back-projection is applied to improve the accuracy of synthesized high-resolution facial image. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to reconstruct high-resolution facial images from low-resolution one captured at a distance.

• Journal of the Korean Wood Science and Technology
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• v.33 no.5 s.133
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• pp.29-37
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• 2005

A previous study verified that the SIRT (simultaneous iterative reconstruction technique) method is more efficient than the back-projection method as a CT algorithm for wood. However, it was expected that the determination of the initial model function of the SIRT method would influence the quality of CT image. Therefore, in this study, we intended to develop a technique that could be used to determine an adequate initial model function. For this purpose, we proposed several techniques, and for each technique we examined the effects of the initial model function on the average errors and the CT image at each iteration. Through this study, it was shown that the average error was decreased and the image quality was improved using the proposed techniques. This tendency was most pronounced when the back-projection method was used to determine the initial model function. From the results of this study, we drew the following conclusions: 1) The initial model function of the SIRT method should be determined with careful attention, and 2) the back-projection method efficiently determines the initial model function of the SIRT method.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.839-842
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• 2000

A new and modified neural network model Is proposed for CT image reconstruction from four projection directions only. The model uses the Resilient Back-Propagation (Rprop) algorithm, which is derived from the original Back-Propagation, for adaptation of its weights. In addition to the error in projection directions of the image being reconstructed, the proposed network makes use of errors in pixels between an image which passed the median filter and the reconstructed one. Improved reconstruction was obtained, and the proposed method was found to be very effective in CT image reconstruction when the given number of projection directions is very limited.

• Journal of the Korean Society of Radiology
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• v.8 no.6
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• pp.357-364
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• 2014

The filtered back projection in the image reconstruction algorithms for the clinic computed tomography system has been widely used. Noise of the reconstructed image was examined under the input noise for parallel and fan beam geometries. The reconstruction images of $512{\times}512$ size were carried out under 360 and 720 projection by the Visual C++ for parallel beam and fan beam, respectively, and those agreed with the original Shepp-Logan head phantom very much. Noise was generated because of intrinsic restriction (finite number of projections) for the image reconstruction algorithm, filtered back projection, when no input noise was applied. Because the result noise was rapidly increased under 0.5% input noise ratio, technologies for reducing noise in CT system and image processing is important.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.4
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• pp.38-45
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• 2001

In this paper, we propose an algorithm for moving object tracking from moving camera using histogram back program intersection(HI) and XY-projection The proposed method segments objects using histogram back projection, matches tracing objects using histogram intersection and extracts them using XY- projection. Through the simulation this paper shows that the proposed method segments. matches and tracks objects without significant error image sequences obtained by moving camera.

• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.266-274
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• 2007

This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on top-down machine learning and recursive error back-projection. A face is represented by a linear combination of prototypes of shape and that of texture. With the shape and texture information of each pixel in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those that of texture by solving least square minimizations. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes. In addition, a recursive error back-projection procedure is applied to improve the reconstruction accuracy of high-resolution facial image. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to reconstruct high-resolution facial images from low-resolution images captured at a distance.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.7
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• pp.81-89
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• 2017

Autofocus(AF) Method is essential to overcome the performance degradation due to motion measurement errors under airborne SAR environment. In this paper, back-projection algorithm(BPA) is applied to SAR raw data acquired under the squinted mode, and preprocessing algorithm of AF for BPA is investigated. To apply AF to SAR image effectively, image backplane rotation method and doppler location alignment function for BPA are proposed. The proposed method is applied to SAR raw data acquired in a flight test and shows excellent performance improvement in real data.