• 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 Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.638-643
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• 2009

A computer-generated hologram(CGH) is made for three-dimensional image reconstruction of a virtual object which is a difficult to irradiate the laser light directly. One of the adverse effect factors is quantization of wave front computed by program when a computer-generated hologram is made. Amplitude element is not considered in Kinoform, it needs processing to reduce noise or false image. So several investigation was reported that the improvement of reconstructed image of Kinoform. Means to calculate the most suitable complex amplitude distribution are iterative algorithm, simulated annealing algorithm and genetic Algorithm. Error diffusion method reconstructed to separate the object as for the noise that originated in the quantization error. So it is efficient method to obtain high quality image with not many processing.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.804-809
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• 2004

It is essential to calibrate a camera in order to recover 3-dimensional reconstruction from uncalibrated images. This paper proposes a new technique of the camera calibration using a homography between the planar patterns image taken by the camera, which is located at the three planar patterns image. Since the proposed method should be computed from the homography among the three planar patterns from a single image, it is implemented more easily and simply to recover 3D object than the conventional. Experimental results show the performances of the proposed method are the better than the conventional. We demonstrate the examples of 3D reconstruction using the proposed algorithm from image sequence.

• Proceedings of the KOSOMBE Conference
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• v.1989 no.05
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• pp.55-59
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• 1989

A true three-dimensional cone-beam reconstruction (TTCR) algorithm for the complete sphere geometry is derived, which is applicable to the direct volume image reconstruction from 2-D cone-beam projections. The algorithm is based on the modified filtered backprojection technique which uses a set of 2-D space-invariant filters and is derived from the previously developed parallel-beam true three-dimensional reconstruction(TTR) algorithm. The proposed algorithm proved to be superior in spatial resolution compared with the parallel-beam TTR algorithm.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.5
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• pp.39-48
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• 2009

Many super-resolution reconstruction algorithms have been proposed since it was the first proposed in 1984. The spatial domain approach of the super-resolution reconstruction methods is accomplished by mapping the low resolution image pixels into the high resolution image pixels. Generally, a super-resolution reconstruction algorithm by using the spatial domain approach has the noise problem because the low resolution images have different noise component, different PSF, and distortion, etc. In this paper, we proposed the new super-resolution reconstruction method that uses the L1 norm to minimize noise source and also uses the Huber norm to preserve edges of image. The proposed algorithm obtained the higher image quality of the result high resolution image comparing with other algorithms by experiment.

• The Transactions of the Korea Information Processing Society
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• v.3 no.2
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• pp.390-398
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• 1996

In this paper, a new image compression algorithm using the generality of the multilaryer perceptron is proposed. Proposed algorithm classifies image into some classes, and trains them through the multilayer perceptron. Multilayer perceptron which trained by the above method can do compression and reconstruction of the nontrained image by the generality. Also, it reduces memory size of the side of receiver and quantization error. For the experiment, we divide Lena image into 16 classes and train them through one multilayer perceptron. The experimental results show that we can get excellent reconstruction images by doing compression and reconstruction for Lena image, Dollar image and Statue image.

• Progress in Medical Physics
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• v.20 no.2
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• pp.62-71
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• 2009

Recently, optical coherence tomography (OCT) has demonstrated considerable promise for the noninvasive assessment of biological tissues. However, OCT images difficult to analyze due to speckle noise. In this paper, we tested various image processing techniques for speckle removal of human and rabbit cartilage OCT images. Also, we distinguished the images which get with methods of image segmentation for OCT images, and found the most suitable method for segmenting an image. And, we selected image segmentation suitable for OCT before image reconstruction. OCT was a weak point to system design and image processing. It was a limit owing to measure small a distance and depth size. So, good edge matching algorithms are important for image reconstruction. This paper presents such an algorithm, the chamfer matching algorithm. It is made of background for 3D image reconstruction. The purpose of this paper is to describe good image processing techniques for speckle removal, image segmentation, and the 3D reconstruction of cartilage OCT images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3460-3467
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• 2013

The In this paper, we have made numerical experiments to compare 2D image reconstruction algorithm of earth model by electrical resistance tomograpy (ERT). Gauss-Newton, simultaneous iterative reconstruction technieque (SIRT) and truncated least squares (TLS) approaches for Wenner and Schlumberger electrode arrays are presented for the solution of the ERT image reconstruction. Computer simulations show that the Gauss-Newton and TLS approach in ERT are proper for 2D image reconstruction of an earth model.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.2
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• pp.75-80
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• 2017

Recently, there has been growing interest in spatial data that combines information and communication technology with smart cities. The high-precision LiDAR (Light Dectection and Ranging) equipment is mainly used to collect three-dimensional spatial data, and the acquired data is also used to model geographic features and to manage plant construction and cultural heritages which require precision. The LiDAR equipment can collect precise data, but also has limitations because they are expensive and take long time to collect data. On the other hand, in the field of computer vision, research is being conducted on the methods of acquiring image data and performing 3D reconstruction based on image data without expensive equipment. Thus, precise 3D spatial data can be constructed efficiently by collecting and processing image data using CCTVs which are installed as infrastructure facilities in smart cities. However, this method can have an accuracy problem compared to the existing equipment. In this study, experiments were conducted and the results were analyzed to increase the number of extracted matching points by applying the feature-based method and the area-based method in order to improve the precision of 3D spatial data built with image data acquired from stereo CCTVs. For techniques to extract matching points, SIFT algorithm and PATCH algorithm were used. If precise 3D reconstruction is possible using the image data from stereo CCTVs, it will be possible to collect 3D spatial data with low-cost equipment and to collect and build data in real time because image data can be easily acquired through the Web from smart-phones and drones.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.145-150
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• 2008

This thesis explores the problem of reconstructing a three-dimensional(3D) scene given a set of images or image sequences of the scene. It describes efficient methods for the 3D reconstruction of static and dynamic scenes from stereo images, stereo image sequences, and images captured from multiple viewpoints. Novel methods for image-based and volumetric modelling approaches to 3D reconstruction are presented, with an emphasis on the development of efficient algorithm which produce high quality and accurate reconstructions. For image-based 3D reconstruction a novel energy minimisation scheme, Iterated Dynamic Programming, is presented for the efficient computation of strong local minima of discontinuity preserving energyy functions. Coupled with a novel morphological decomposition method and subregioning schemes for the efficient computation of a narrowband matching cost volume. the minimisation framework is applied to solve problems in stereo matching, stereo-temporal reconstruction, motion estimation, 2D image registration and 3D image registration. This thesis establishes Iterated Dynamic Programming as an efficient and effective energy minimisation scheme suitable for computer vision problems which involve finding correspondences across images. For 3D reconstruction from multiple view images with arbitrary camera placement, a novel volumetric modelling technique, Embedded Voxel Colouring, is presented that efficiently embeds all reconstructions of a 3D scene into a single output in a single scan of the volumetric space under exact visibility. An adaptive thresholding framework is also introduced for the computation of the optimal set of thresholds to obtain high quality 3D reconstructions. This thesis establishes the Embedded Voxel Colouring framework as a fast, efficient and effective method for 3D reconstruction from multiple view images.