• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.2
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• pp.157-169
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• 2013

Scale Invariant Feature Transform (SIFT) generates image features widely used to match objects in different images. Previous work on hardware-based SIFT implementation requires excessive internal memory and hardware logic [1]. In this paper, a new hardware organization is proposed to implement SIFT with less memory and hardware cost than the previous work. To this end, a parallel Gaussian filter bank is adopted to eliminate the buffers that store intermediate results because parallel operations allow all intermediate results available at the same time. Furthermore, the processing order is changed from the raster-scan order to the block-by-block order so that the line buffer size storing the source image is also reduced. These techniques trade the reduction of memory size with a slight increase of the execution time and external memory bandwidth. As a result, the memory size is reduced by 94.4%. The proposed hardware for SIFT implementation includes the Descriptor generation block, which is omitted in the previous work [1]. The addition of the hardwired descriptor generation improves the computation speed by about 30 times when compared with the previous work.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.66-69
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• 2002

This article outlines the capabilities of a viewer component called GridViewer, and proves its reusability. GridViewer was designed for the construction of the image display part of GIS or remote sensing application software, and consequently it is particularly straightforward to closely couple GridViewer with access to very large images. Displaying is performed through pyramid structure, which enables to treat very large dataset up to several gigabytes in size under the limited capability of PC. GridViewer is free from responsibility to handle various formats of raster data files by taking grid coverage, which is designed by OGC to promote interoperability between implementations done by data vendors and software vendors providing analysis and grid processing implementations. GridViewer differs from other such viewer by allowing for clients to extend its function and capability by using small set of methods originally implemented in it. We show its reusability and expandability by applying it in developing application programs performing various functions not supported originally by the GridViewer COM component.

• Journal of Biomedical Engineering Research
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• v.14 no.1
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• pp.9-16
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• 1993

For efficient storage and transmission of medical images, the requirement of image com pression is increasing. Because differences between reconstructed images and original images are related with errors In the diagnosis, lossless compression is generally preferred in mod- ical images. in Run Length Coding which is one of the lossless compression method, we have applied modified scanning direction based on the Hilbert curve, which is a kind of space fill ins curve. We have substituted the traditional raster scanning by Hilbert curve direction scanning. Using this method, we have studied enhancement of compression efficiency for medical images.

• ETRI Journal
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• v.26 no.4
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• pp.332-343
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• 2004

One of the recent and most significant technical properties can be expressed as "digital convergence," which is helping lead the technical paradigm into a ubiquitous environment. As an initial trial of realizing a ubiquitous environment, the convergence between broadcasting and telecommunication fields is now on the way, where it is required to develop a scalable video coding scheme for one-source and multi-use media. Traditional scalable video coding schemes have, however, limitations for higher stable picture quality especially on the region of interest. Therefore, this paper introduces an adaptive scanning method especially designed for a higher regional-stable picture quality under a ubiquitous video coding environment, which can improve the subjective quality of the decoded video by most-preferentially encoding, transmitting, and decoding the top-priority image information of the region of interest. Thus, the video can be more clearly visible to users. From various simulation results, the proposed scanning method in this paper can achieve an improved subjective picture quality far better than the widely used raster scan order in conventional video coding schemes, especially on the region of interest, and without a significant loss of quality in the left-over region.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.789-792
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• 2010

최근 다양하게 활용되고 있는 수치지도 기반의 지도 영상은 그 신속성과 정확성이 가장 중요시되고 있다. 특히, 공군에서 사용하고 있는 지도영상 자료 활용 시스템인 비행 임무 계획 시스템의 상황도 시현 시, 대용량 래스터 데이터(Raster Data)를 처리해야 하는데, 지도의 종류가 다양해지고, 정밀해질수록 시스템의 효율적인 구동에 한계가 발생되고 있는 현실이며, 처리하는 영상의 호환성 및 왜곡현상의 문제점도 함께 야기되고 있다. 이에 본 연구에서는 ARC System 및 RPF Naming Rule을 적용하여 대용량 래스터 데이터 처리과정을 개선하고, 호환성을 보장하며, 왜곡현상을 줄이는 효율적인 지도 영상 처리방안을 제안한다.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.42.1-42.1
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• 2019

We investigate a collapsing granule event and the associated excitation of waves in the photosphere and chromosphere. Our observations were carried out by using the Fast Imaging Solar Spectrograph and the TiO 7057Å Broadband Filter Imager of the 1.6 meter Goode Solar Telescope of Big Bear Solar Observatory. During our observations, we found a granule which became significantly darker than neighboring granules. The edge of the granule collapsed within several minutes. After the collapse, transient oscillations occurred in the photospheric and chromospheric layers. The dominant period of the oscillations is close to 4.5 minutes in the photosphere and 4 minutes in the chromosphere. Moreover, in the Ca II-0.5Å raster image, we observed brightenings which are considered as the manifestation of shock waves. Based on our results, we suggest that the impulsive collapse of a granule can generate upward-propagating acoustic waves in the solar quiet region that ultimately develop into shocks.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.1
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• pp.47-52
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• 2008

The visual implementation of 3-dimensional national environment is focused by the requirement and importance in the fields such as, urban planing, telecommunication facility deployment plan, railway construction, construction engineering, spatial city development, safety and disaster prevention engineering. The currently used DEM system based on the 2-D digital maps and contour lines has limitation in implementation in reproducing the 3-D spatial city. Currently, the LiDAR data which combines the laser and GPS skill has been introduced to obtain high resolution accuracy in the altitude measurement in the advanced country. In this paper, we first introduce the LiDAR based researches in advanced foreign countries, then we propose the data generation scheme and an solution algorithm for the optimal management of our 3-D spatial u-City construction. For this purpose, LiDAR based height data transformed to DEM, and the realtime unification of the vector via digital image mapping and raster via exactness evaluation is transformed to make it possible to trace the model of generated 3-dimensional model with long distance for 3D u-city model generation.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.41-50
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• 1999

In this paper, the new VLSI architecture of a reconstruction filter for morphological image segmentation is proposed. The filter, based on the $h_{max}$ operation, simplifies the interior of each region while preserving the boundary information. The proposed architecture adopts a partitioned memory structure and an efficient image scanning strategy to reduce the operations. The proposed memory partitioning scheme makes it possible that every data required for processing can be read from each memory at a time, resulting in parallel data processing. By the extended connectivity consideration, the operation is much decreased because more simplification is achieved in scanning stage. The selective raster scan strategy endows the satisfactory noise removal capability with negligible hardware complexity increase. The proposed architecture is designed using VHDL, and functional evaluation is performed by the CAD tool, Mentor. The experiment results show that the proposed architecture can simplify image profile with less than 18% operations of the conventional method.

• Spatial Information Research
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• v.14 no.1 s.36
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• pp.151-161
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• 2006

This paper has a goal to construct monitoring web GIS system which displays maps that are results of the fire detecting algorithms using MODIS image. To design and build more efficient system, foreign fire monitoring systems using satellite image are researched and analyzed. As a result of that, the information about interfaces and services provided by them are obtained. In concretely, new logical DFD is used to do a process modelling. ArcIMS 4.0 of ESRI, IIS 5.1 of Microsoft are utilized to build the web GIS System. In the aspects of data input and transfer, a specific module, which converts a binary image to a kind of vector file, is developed to adjust raster data to the web GIS system.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.269-282
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• 2023

The purpose of this study was to construct land cover maps using a deep learning model and to select the optimal deep learning model for land cover classification by adjusting the dataset such as input image size and Stride application. Two types of deep learning models, the U-net model and the DeeplabV3+ model with an Encoder-Decoder network, were utilized. Also, the combination of the two deep learning models, which is an Ensemble model, was used in this study. The dataset utilized RapidEye satellite images as input images and the label images used Raster images based on the six categories of the land use of Intergovernmental Panel on Climate Change as true value. This study focused on the problem of the quality improvement of the dataset to enhance the accuracy of deep learning model and constructed twelve land cover maps using the combination of three deep learning models (U-net, DeeplabV3+, and Ensemble), two input image sizes (64 × 64 pixel and 256 × 256 pixel), and two Stride application rates (50% and 100%). The evaluation of the accuracy of the label images and the deep learning-based land cover maps showed that the U-net and DeeplabV3+ models had high accuracy, with overall accuracy values of approximately 87.9% and 89.8%, and kappa coefficients of over 72%. In addition, applying the Ensemble and Stride to the deep learning models resulted in a maximum increase of approximately 3% in accuracy and an improvement in the issue of boundary inconsistency, which is a problem associated with Semantic Segmentation based deep learning models.