Abstract:
2차원 영상으로부터 3차원 영상을 재구성하는 방법 및 장치가 제공된다. 제한된 각도에서 엑스선(x-ray) 발생 튜브로부터 재구성되는 3차원 데이터를, 각 화소별로 반복적으로 갱신하고, 복원하기 위해서 투영된 데이터의 각 화소들 중에서 중앙값(median)을 선택하며, 재투영된 영상 및 나머지 영상을 이용한 탐색 방향 가중치를 이용하여 역투영하여, 복원 데이터의 희소성(sparsity) 구속 조건과 L1 놈 충실성(fidelity)이 있는 데이터 조건을 만족하는 3차원 영상을 재구성할 수 있다. 엑스선(x-ray), 영상 재구성(tomosynthesis), L1 놈 충실성(fidelity) 데이터, 데이터의 희소성(sparsity)
Abstract:
감마선 산란 사이노그램을 생성하여 영상을 재구성하기 위한 방법 및 장치가 제공된다. 초기의 산란 보정이 되지 않은 재구성 영상에서, 광자의 발생 위치가 결정된다. GPU는 몬테카를로 시뮬레이션을 사용하여 광자의 이동을 연산한다. 광자가 검출기에 도달한 위치를 통해 3차원 측정선이 계산되며, 계산된 측정선은 3차원 사이노그램 형식으로 변환되어 프롬프트 사이노그램 및 감마선 산란 사이노그램에 저장된다. 감마선 산란 사이노그램의 스케일을 조정함으로써 최종적인 감마선 산란 사이노그램이 생성된다.
Abstract:
PURPOSE: A compressive DOT(Diffuse Optical Tomography) method and an apparatus thereof are provided to quickly and accurately restore images by restoring the images using joint scarcity. CONSTITUTION: A DOT problem is converted to MMV(Multiple Measurement Vector) by using joint scarcity(S210). An active index set is calculated by using an MMV algorithm(S220). The amount of changed absorption coefficient is calculated by using a least square fitting algorithm(S230). [Reference numerals] (AA) Start; (BB) End; (S210) Converting a DOT problem to an MMV problem by using joint scarcity; (S220) Calculating an active index set by using MMV algorithm; (S230) Calculating the change amount of an absorption coefficient by using least square fitting algorithm
Abstract:
PURPOSE: An ultra resolution microscope system and an image obtaining method using the same are provided to obtain an image in ultra resolution of a nanometer degree by using an irregular pattern and an alignment signal processing technique. CONSTITUTION: A scattering pattern generator(110) passes transmitted light through a scattering unit to photograph fluorescent light sources of an object. An incident optical system(120) inserts a scattering pattern generated by one or more optical lenses into a specimen. A fluorescent optical image system(130) passes the inserted scattering pattern through one or more excitation filters and fluorescent filters in order. [Reference numerals] (110) Scattering pattern generator; (120) Incident optical system; (130) Fluorescent optical image system; (140) Image restoration algorithm
Abstract:
PURPOSE: A tera-hertz time domain spectral device and an image processing method are provided to obtain higher resolution of image with a smaller number of samples by employing compression sensing theory instead of radon transform. CONSTITUTION: A tera-hertz time domain spectral device(100) comprises an optical system and an adjustment system. The optical system employs tera-hertz beam as light source and forms a two-dimensional image using time domain. The adjustment system forms a mask(4) transforming Fourier domain on the optical system. The optical system restores the original two-dimensional object from one-dimension time data which is obtained by rotating the mask.
Abstract:
PURPOSE: An image reconstruction system in a three dimensional space using terahertz pulse-echo and a method thereof are provided to restore a location of an object in a three dimensional space using a pulse wave of terahertz, thereby obtaining an image with improved resolution. CONSTITUTION: An optical system irradiates a pulse wave of a terahertz area to a three dimensional space. The optical system receives a reflecting wave reflected by a diffused object of a three dimensional space. An image restoring unit(130) applies a compression sensing algorithm to restore a location of the diffused object from the received reflected wave. The optical system is composed of a photo-electron antenna(110). A pulse generating unit(111) generates a pulse wave. A pulse receiving unit(113) receives the reflected wave.
Abstract:
PURPOSE: A method and an apparatus for regenerating a three-dimensional image from a two-dimensional image are provided to improve a noise removal effect compared with a linear filtering method by processing images through a non-linear filtering method according to a median value. CONSTITUTION: A recovery image generator(310) creates a three-dimensional recovery image through reverse projection using a pixel value corresponding to a median value among pixel values of images. The images are created by the two-dimensional projection of a target to be three-dimensionally recovered. A re-projection image generator(320) creates a two-dimensional re-projected image through the re-projection of the three-dimensional recovered image. A residual image forming part(330) constitutes a residual image according to the difference between the projected image and the two-dimensional re-projected image.
Abstract:
A method for restoring an image is provided to achieve the restoration to a high-resolution image, by applying an FOCUSS(Focal Underdetermined System Solver) algorithm to a low-resolution image frequency data, which are converted from down-sampled data. Down-sampled data are outputted with respect to an image having a dynamic change(S10). The down-sampled data are converted into low-resolution image frequency data(S20). The converted low-resolution image frequency data are converted into a high-resolution image by applying an FOCUSS algorithm in a k-t space(S30). The down-sampled data are converted into the low-resolution image frequency data by using second-dimensional Fourier transformation.