• Korean Journal of Remote Sensing
• /
• v.33 no.4
• /
• pp.339-350
• /
• 2017

In recent, cloud computing paradigm and open source as a huge trend in the Information Communication Technology (ICT) are widely applied, being closely interrelated to each other in the various applications. The integrated services by both technologies is generally regarded as one of a prospective web-based business models impacting the concerned industries. In spite of progressing those technologies, there are a few application cases in the geo-based application domains. The purpose of this study is to develop a cloud-based service system for satellite image processing based on the pure and full open source. On the OpenStack, cloud computing open source, virtual servers for system management by open source stack and image processing functionalities provided by OTB have been built or constructed. In this stage, practical image processing functions for KOMPSAT within this service system are thresholding segmentation, pan-sharpening with multi-resolution image sets, change detection with paired image sets. This is the first case in which a government-supporting space science institution provides cloud-based services for satellite image processing functionalities based on pure open source stack. It is expected that this implemented system can expand with further image processing algorithms using public and open data sets.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10b
• /
• pp.1758-1763
• /
• 1991

This paper describes a new method to determine the 3D-shape of objects consisting of specular planar surfaces. This method exploits a light source which is made of a diffuse plane with a grid pattern encoded in an M-sequence and uses a single image of the light source reflected by the objects to acquiring orientations and positions of the surfaces of the objects. When grid lines of the light source are reflected by a specular planar surface and perspectively projected on an image plane, a set of lines vanishing at a point are obtained on the image plane. The orientation of the specular planar surface is determined by using the vanishing point, and the position is determined by using the correspondence between lines on the image and lines on the light source, which is obtained by employing a characteristic regularity of the M-sequence. Before the vanishing points are calculated, the lines on the image are classified and correlated with the surfaces of objects by using slopes and positions of the lines and the regularity of the M-sequence. This method requires only a single image.

• Journal of Information Processing Systems
• /
• v.12 no.2
• /
• pp.322-331
• /
• 2016

Image compression is an essential technique for saving time and storage space for the gigantic amount of data generated by images. This paper introduces an adaptive source-mapping scheme that greatly improves bit-level lossless grayscale image compression. In the proposed mapping scheme, the frequency of occurrence of each symbol in the original image is computed. According to their corresponding frequencies, these symbols are sorted in descending order. Based on this order, each symbol is replaced by an 8-bit weighted fixed-length code. This replacement will generate an equivalent binary source with an increased length of successive identical symbols (0s or 1s). Different experiments using Lempel-Ziv lossless image compression algorithms have been conducted on the generated binary source. Results show that the newly proposed mapping scheme achieves some dramatic improvements in regards to compression ratios.

• Journal of Information Processing Systems
• /
• v.19 no.6
• /
• pp.858-869
• /
• 2023

As one of the pivotal techniques of image restoration, single-channel blind source separation (SCBSS) is capable of converting a visual-only image into multi-source images. However, image degradation often results from multiple mixing methods. Therefore, this paper introduces an innovative SCBSS algorithm to effectively separate source images from a composite image in various mixed modes. The cornerstone of this approach is a novel triple generative adversarial network (TriGAN), designed based on dual learning principles. The TriGAN redefines the discriminator's function to optimize the separation process. Extensive experiments have demonstrated the algorithm's capability to distinctly separate source images from a composite image in diverse mixed modes and to facilitate effective image restoration. The effectiveness of the proposed method is quantitatively supported by achieving an average peak signal-to-noise ratio exceeding 30 dB, and the average structural similarity index surpassing 0.95 across multiple datasets.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.6 no.4
• /
• pp.217-223
• /
• 2010

In the case of image magnification by using interpolation methods, interpolated pixels are estimated from the known pixels in source image. The magnified image is composed of the known pixels in source image and the interpolated pixels which is estimated. If the interpolated pixels are estimated to have the locality which is exists in real images, the magnified image is much closer to the real image. In this paper, an improved interpolation scheme is proposed to estimate pixels from the known pixels in source image using the locality which is exists in real images. The magnified image by using the proposed interpolation scheme is much closer to the real image. The performance of the proposed interpolation scheme is evaluated by using PSNR(Peak Signal to Noise Ratio) in experiment. The PSNR of the magnified image by using the proposed scheme is improved than that of the magnified images by using existing interpolation methods. So, the proposed interpolation scheme is an efficient interpolation method for the quality improvement of magnified image.

• Journal of Ocean Engineering and Technology
• /
• v.9 no.2
• /
• pp.75-82
• /
• 1995

The free surface effects on the aerodynamic performance of 2-D wings are investigated based on the potential flow approximation. The wing is represented b source and vortex distributions on the wing surface. The steady free surface effect is taken into account by source distribution on the free surface and the velocity potentials of air and water flows are obtained. Using three different techniques, namely, positive image method, inverse image method and source distribution method, numerical results are obtained for wave elevation, pressure distribution and lift coefficient with various foil sections. The wave elevation calculated by the inverse image method is shown to be very small even at higher speeds so that the free surface effect on the performance of wings is regraded negligible. However, the wave elevations by the positive image method and source distribution method are relatively high at higher speeds and accordingly the free surface effects on wings can not be neglected.

• Journal of KSNVE
• /
• v.7 no.2
• /
• pp.255-260
• /
• 1997

This paper describes 3-dimensional volume array of 4 microphones including a reference microphone which is capable of imaging wideband noise source position in 2-dimensional image plane. The cross correlation function and corresponding imaging function between a reference microphone and other microphone, are derived as a function of noise source position. The magnitude of the imaging function gives noise source mapping in image plane. Since the image plane is selective from a rectangular and a cylindrical plane, noise source position information such as range and bearing relative to the array is identified very much easily. Simulation results for typical source configurations confirms the applicability of the proposed array in noise control field.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.7
• /
• pp.3268-3283
• /
• 2018

With the advent of the Information Age, the source identification of digital images, as a part of digital image forensics, has attracted increasing attention. Therefore, an effective technique to identify the source of digital images is urgently needed at this stage. In this paper, first, we study and implement some previous work on image source identification based on sensor pattern noise, such as the Lukas method, principal component analysis method and the random subspace method. Second, to extract a purer sensor pattern noise, we propose a sample selection method to improve the random subspace method. By analyzing the image texture feature, we select a patch with less complexity to extract more reliable sensor pattern noise, which improves the accuracy of identification. Finally, experiment results reveal that the proposed sample selection method can extract a purer sensor pattern noise, which further improves the accuracy of image source identification. At the same time, this approach is less complicated than the deep learning models and is close to the most advanced performance.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.117-120
• /
• 1996

In this paper, a new approach to acquire the cross-sentional image for automatic solder joint inspection of double-sided PCB using X-ray source is presented. We designed the apparatus with fixed X-ray source to realize the cross-sectional image by tunning object and detector synchronously. The cross-sectional images are captured at several view angle of X-ray source, the geometric image distortions caused by view angle and the shape of image intensifier are compensated. The precision variation of cross-sectional image by the change of view angle was investigated. Also we acquired the cross-sectional image to the solder joint of double-sided PCB and reconstructed the shape of solder joint.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.229-233
• /
• 2007

This study is to test the applicability of QuickBird image for non-point source pollution assessment. SWAT (Soil and Water Assessment Tool) model was adopted and the model was calibrated for a stream watershed of 255.4 $km^2$ Landsat land use data. For model application with QuickBird image, a precise agricultural land use map of 1.16 $km^2$ area located in the upstream watershed was produced by field investigation. The model was run with the combination of land use and soil map scales (1:5,000, 1:25,000 and 1:50,000). The results were compared and analyzed for the contribution of non-point source pollution by the land use scale and contents.