• Journal of IKEEE
• /
• v.25 no.1
• /
• pp.76-82
• /
• 2021

In this paper, the compressed sensing basic pursuit denoise algorithm adopted to synthetic aperture radar imaging is investigated to improve the object recognition. From the incomplete data sets for image processing, the compressed sensing algorithm had been integrated to recover the data before the conventional back- projection algorithm was involved to obtain the synthetic aperture radar images. This method can lead to the reduction of measurement events while scanning the objects. An ultra-wideband radar scheme using a stripmap synthetic aperture radar algorithm was utilized to detect objects hidden behind the box. The Ultra-Wideband radar system with 3.1~4.8 GHz broadband and UWB antenna were implemented to transmit and receive signal data of two conductive cylinders located inside the paper box. The results confirmed that the images can be reconstructed by using a 30% randomly selected dataset without noticeable distortion compared to the images generated by full data using the conventional back-projection algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.1
• /
• pp.33-45
• /
• 2011

In this paper, we present a method for extracting video objects efficiently by using the modified graph cut algorithm based on contour information. First, we extract objects at the first frame by an automatic object extraction algorithm or the user interaction. To estimate the objects' contours at the current frame, motion information of objects' contour in the previous frame is analyzed. Block-based histogram back-projection is conducted along the estimated contour point. Each color model of objects and background can be generated from back-projection images. The probabilities of links between neighboring pixels are decided by the logarithmic based distance transform map obtained from the estimated contour image. Energy of the graph is defined by predefined color models and logarithmic distance transform map. Finally, the object is extracted by minimizing the energy. Experimental results of various test images show that our algorithm works more accurately than other methods.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.21 no.1
• /
• pp.17-24
• /
• 2018

Polar fomat algorithm (PFA) was derived from medical imaging theory, known as back projection, to process synthetic aperture radar(SAR) data. The difference between the operating condition of SAR and back projection assumption makes two distortions. First, the focusing performance of PFA is degraded in proportion to distances from the scene center. Second, the geometric accuracy in SAR images is distorted. Several methods were introduced to mitigate the distortions, but some disadvantages, such as the geometric discontinuity, are arisen when sub-images are combined. This paper proposes the novel method to compensate the geometric distortion with chirp Z-transform (CZT). This method corrects precisely the geometric errors without any problems, because a whole image can be processed all at once.

• Journal of Sensor Science and Technology
• /
• v.19 no.2
• /
• pp.118-123
• /
• 2010

This paper proposes super-resolution reconstruction algorithm for image enhancement. Super-resolution reconstruction algorithms reconstruct a high-resolution image from multi-frame low-resolution images of a scene. Conventional super- resolution reconstruction algorithms are iterative back-projection(IBP), robust super-resolution(RS)method and standard Papoulis-Gerchberg(PG)method. However, traditional methods have some problems such as rotation and ringing. So, this paper proposes modified algorithm to improve the problem. Experimental results show that this proposed algorithm solve the problem. As a result, the proposed method showed an increase in the PSNR for traditional super-resolution reconstruction algorithms.

• Proceedings of the Korean Society of Medical Physics Conference
• /
• 2002.09a
• /
• pp.439-441
• /
• 2002

The aim of this study is to reconstruct the 3D target volume from multiple projection images. It was assumed that we were already aware of the target position exactly, and all processes were performed in Target Coordinates whose origin was the center of the target. We used six projections: two projections were used to make a Reconstruction Box and four projections were for image acquisition. Reconstruction Box was made up of voxels of 3D matrix. Projection images were transformed into 3D volume in this virtual box using geometrical based back-projection method. Algorithm was applied to an ellipsoid model and horse-shoe shaped model. Projection images were created using C program language by geometrical method and reconstruction was also accomplished using C program language and Matlab(The Mathwork Inc., USA). For ellipsoid model, reconstructed volume was slightly overestimated but target shape and position was proved to be correct. For horse-shoe shaped model, reconstructed volume was somewhat different from original target model but there was a considerable improvement in target volume determination.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.28 no.9
• /
• pp.723-732
• /
• 2017

Simplified factorizing-technique to improve the efficiency on computational procedure and the complexity of the conventional back-projection algorithm, which is used to reconstruct airborne FMCW-SAR image, is suggested, and the reconstruction process of SAR image by this simplified factorizing-technique are presented in this paper. This technique can be efficiently applied to airborne FMCW-SAR having a relatively narrow beamwidth and long synthetic aperture length, and its basic rationale is to exclude the data that has low level of contribution during computational procedure. Using the raw data of practical airborne FMCW-SAR system, performances of this proposed technique such as SAR image quality and processing time were compared and analyzed.

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

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.1
• /
• pp.41-46
• /
• 2023

Iterative reconstruction of CT takes a long time because projection and back-projection are alternatively repeated until taking a good image. To reduce the reconstruction time, we need a fast algorithm for calculating the projection which is a time-consuming step. In this paper, we proposed a new algorithm to calculate the line integral and the algorithm is approximately 10% faster than the well-known Siddon method (Jacobs version) and has a good image quality. Although the algorithm has been investigated for the case of parallel beams, it can be extended to the case of fan and cone beam geometries in the future.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.19 no.10
• /
• pp.1175-1184
• /
• 2008

Delay-sum back projection(DSBP) algorithm and the time reversal algorithm based on the finite-difference time-domain method are compared. The two algorithms, which operate in the time domain, can process the ultra-wideband (UWB) radar data to generate images that are close to the original location and shape of the target. For the experiment, the UWB radar consists of a network analyzer, a resistive V dipole antenna, a scanner, and a control computer. The radar aperture is synthesized by linearly scanning the antenna. A calibration procedure is applied to the measured data to remove signal distortion and clutter. The two algorithms are applied to the same data on the same platform. It is shown that the DSBP algorithm produces better images but takes longer time to produce the images than the FDTD-TR algorithm.

• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.10
• /
• pp.377-382
• /
• 2018

This study deals with internal state and tissue density analysis methods for red ginseng grade determination. For internal measurement of red ginseng, there have been various studies on nondestructive testing methods since the 1990s, It was difficult to grasp the most important inner hole and inside whites in the grading. So in this study, we developed a closed capturing device for infra-red illumination environment, and developed an internal measurement system that can detect the presence and diameter of inner hole and inside whites. Made devices consisted of infrared lights with a high transmission rate of red ginseng in 920 nanometer wave band, a infra-red camera and a Y axis actuator with a red ginseng automatically controlled focus on the camera. The proposed algorithm performs an auto-focus system on the Y-axis actuator to automatically adjust the sharp focus of the object according to the size and thickness. Then red ginseng is rotated $360^{\circ}$ at $1^{\circ}$ intervals and 360 total images are acquired, and reconstructed as a sinogram through Radon transform and Back-projection algorithm was performed to acquire internal images of red ginseng. As a result of the algorithm, it was possible to acquire internal cross-sectional image regardless of the thickness and shape of red ginseng. In the future, if more than 10,000 different shapes and sizes of red ginseng internal cross-sectional image are acquired and the classification criterion is applied, it can be used as a reliable automated ginseng grade automatic measurement method.