• Title/Summary/Keyword: Computational Reconstruction

Search Result 271, Processing Time 0.022 seconds

Computational integral imaging reconstruction method using round-type mapping model (원형 매핑 모델을 사용하는 컴퓨터 직접 영상 재생 방식)

  • Sin, Dong-Hak;Kim, Nam-Woo;Lee, Jun-Jae;Lee, Byeong-Guk
    • Proceedings of the Optical Society of Korea Conference
    • /
    • 2007.07a
    • /
    • pp.259-260
    • /
    • 2007
  • In this paper, we propose a novel computational integral imaging reconstruction (CIIR) method using round-type mapping model. Proposed CIIP method can overcome problems of non-uniformly reconstructed images caused from the conventional method and improve the resoulution of 3-D images. To show the usefulness of the proposed method, both computational experiment and optical experiment are carried out and their results are presented.

  • PDF

Resolution-improved 3D volumetric computational reconstruction using smart pixel mapping

  • Tan, Chun-Wei;Shin, Dong-Hak;Lee, Byung-Gook
    • Proceedings of the Optical Society of Korea Conference
    • /
    • 2008.02a
    • /
    • pp.181-182
    • /
    • 2008
  • In this paper, we propose a volumetric computational reconstruction method by use of smart pixel mapping technique in the computational integral imaging in order to overcome the problem of resolution degradation. The experimental results are presented to show the usefulness of our proposed technique.

  • PDF

Fast Iterative Solving Method of Fuzzy Relational Equation and its Application to Image Compression/Reconstruction

  • Nobuhara, Hajime;Takama, Yasufumi;Hirota, Kaoru
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • v.2 no.1
    • /
    • pp.38-42
    • /
    • 2002
  • A fast iterative solving method of fuzzy relational equation is proposed. It is derived by eliminating a redundant comparison process in the conventional iterative solving method (Pedrycz, 1983). The proposed method is applied to image reconstruction, and confirmed that the computation time is decreased to 1 / 40 with the compression rate of 0.0625. Furthermore, in order to make any initial solution converge on a reconstructed image with a good quality, a new cost function is proposed. Under the condition that the compression rate is 0.0625, it is confirmed that the root mean square error of the proposed method decreases to 27.34% and 86.27% compared with those of the conventional iterative method and a non iterative image reconstruction method, respectively.

Improved Viewing Quality of 3-D Images in Computational Integral Imaging Reconstruction Based on Round Mapping Model

  • Shin, Dong-Hak;Kim, Nam-Woo;Yoo, Hoon;Lee, Joon-Jae;Lee, Byoung-Ho;Kim, Eun-Soo
    • ETRI Journal
    • /
    • v.29 no.5
    • /
    • pp.649-654
    • /
    • 2007
  • In this paper, we propose a computational integral imaging reconstruction (CIIR) method using a round mapping model to improve the viewing quality of 3-D images. The proposed CIIR method can overcome the problem of non-uniformly reconstructed images caused by the conventional method. To show the usefulness of proposed method, some experiments are carried out and the results are presented.

  • PDF

2D Design Feature Recognition using Expert System (전문가 시스템을 이용한 2차원 설계 특징형상의 인식)

  • 이한민;한순흥
    • Korean Journal of Computational Design and Engineering
    • /
    • v.6 no.2
    • /
    • pp.133-139
    • /
    • 2001
  • Since a great number of 2D engineering drawings are being used in industry and at the same time 3D CAD becomes popular in recent years, we need to reconstruct 3D CAD models from 2D legacy drawings. In this thesis, a combination of a feature recognition method and an expert system is suggested for the 3D solid model reconstruction. Modeling primitives of 3D CAD systems are recognized and constructed by using the pattern matching technique of the features modeling. Additional information for the 3D model reconstruction can be generated by extracting symbols or text entities which are related to form entities. For complex and indefinite cases which cannot be solved by the process of feature recognition, an expert system with a rule base has been used for decision-making. A 3D reconstruction system which recognizes 2D DXF drawing files has been implemented where models composed with protrusions, holes, and cutouts can be handled.

  • PDF

Coupled Line Cameras as a New Geometric Tool for Quadrilateral Reconstruction (사각형 복원을 위한 새로운 기하학적 도구로서의 선분 카메라 쌍)

  • Lee, Joo-Haeng
    • Korean Journal of Computational Design and Engineering
    • /
    • v.20 no.4
    • /
    • pp.357-366
    • /
    • 2015
  • We review recent research results on coupled line cameras (CLC) as a new geometric tool to reconstruct a scene quadrilateral from image quadrilaterals. Coupled line cameras were first developed as a camera calibration tool based on geometric insight on the perspective projection of a scene rectangle to an image plane. Since CLC comprehensively describes the relevant projective structure in a single image with a set of simple algebraic equations, it is also useful as a geometric reconstruction tool, which is an important topic in 3D computer vision. In this paper we first introduce fundamentals of CLC with reals examples. Then, we cover the related works to optimize the initial solution, to extend for the general quadrilaterals, and to apply for cuboidal reconstruction.

Three-Dimensional Photon Counting Imaging with Enhanced Visual Quality

  • Lee, Jaehoon;Lee, Min-Chul;Cho, Myungjin
    • Journal of information and communication convergence engineering
    • /
    • v.19 no.3
    • /
    • pp.180-187
    • /
    • 2021
  • In this paper, we present a computational volumetric reconstruction method for three-dimensional (3D) photon counting imaging with enhanced visual quality when low-resolution elemental images are used under photon-starved conditions. In conventional photon counting imaging with low-resolution elemental images, it may be difficult to estimate the 3D scene correctly because of a lack of scene information. In addition, the reconstructed 3D images may be blurred because volumetric computational reconstruction has an averaging effect. In contrast, with our method, the pixels of the elemental image rearrangement technique and a Bayesian approach are used as the reconstruction and estimation methods, respectively. Therefore, our method can enhance the visual quality and estimation accuracy of the reconstructed 3D images because it does not have an averaging effect and uses prior information about the 3D scene. To validate our technique, we performed optical experiments and demonstrated the reconstruction results.

3D Image Correlator using Computational Integral Imaging Reconstruction Based on Modified Convolution Property of Periodic Functions

  • Jang, Jae-Young;Shin, Donghak;Lee, Byung-Gook;Hong, Suk-Pyo;Kim, Eun-Soo
    • Journal of the Optical Society of Korea
    • /
    • v.18 no.4
    • /
    • pp.388-394
    • /
    • 2014
  • In this paper, we propose a three-dimensional (3D) image correlator by use of computational integral imaging reconstruction based on the modified convolution property of periodic functions (CPPF) for recognition of partially occluded objects. In the proposed correlator, elemental images of the reference and target objects are picked up by a lenslet array, and subsequently are transformed to a sub-image array which contains different perspectives according to the viewing direction. The modified version of the CPPF is applied to the sub-images. This enables us to produce the plane sub-image arrays without the magnification and superimposition processes used in the conventional methods. With the modified CPPF and the sub-image arrays, we reconstruct the reference and target plane sub-image arrays according to the reconstruction plane. 3D object recognition is performed through cross-correlations between the reference and the target plane sub-image arrays. To show the feasibility of the proposed method, some preliminary experiments on the target objects are carried out and the results are presented. Experimental results reveal that the use of plane sub-image arrays enables us to improve the correlation performance, compared to the conventional method using the computational integral imaging reconstruction algorithm.