• Proceedings of the KSRS Conference
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• v.2
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• pp.647-650
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• 2006

Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery was acquired over the Little Miami River Watershed (1756 square miles) in Ohio, U.S.A., which is one of the largest hyperspectral image acquisition. For the development of a 4m-resolution land cover dataset, a hierarchical approach was employed using two different classification algorithms: 'Image Object Segmentation' for level-1 and 'Spectral Angle Mapper' for level-2. This classification scheme was developed to overcome the spectral inseparability of urban and rural features and to deal with radiometric distortions due to cross-track illumination. The land cover class members were lentic, lotic, forest, corn, soybean, wheat, dry herbaceous, grass, urban barren, rural barren, urban/built, and unclassified. The final phase of processing was completed after an extensive Quality Assurance and Quality Control (QA/QC) phase. With respect to the eleven land cover class members, the overall accuracy with a total of 902 reference points was 83.9% at 4m resolution. The dataset is available for public research, and applications of this product will represent an improvement over more commonly utilized data of coarser spatial resolution such as National Land Cover Data (NLCD).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.17-25
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• 2007

In most electronic imaging applications, image with high resolution(HR) are desired. HR means that pixel density within an image is high, and therefore HR image can offer more details that may be critical in various applications. Digital images that are captured by CCD and CMOS cameras usually have a very low resolution, which significantly limits the performance of image recognition systems. Image super-resolution techniques can be applied to overcome the limits of these imaging systems. Super-resolution techniques have been proposed to increase the resolution by combining information from multiple images. To techniques were consisted of the registration algorithm for estimation and shift, the nearest neighbor interpolation using weight of acquired frames and presented frames. In this paper, it is proposed the image interpolation techniques using the wavelet base function. This is applied to embody a correct edge image and natural image when expend part of the still image by applying the wavelet base function coefficient to the conventional Super-Resolution interpolation method. And the proposal algorithm in this paper is confirmed to improve the image applying the nearest neighbor interpolation algorithm, bilinear interpolation algorithm.,bicubic interpolation algorithm through the computer simulation.

• Journal of radiological science and technology
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• v.45 no.2
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• pp.117-125
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• 2022

Although stationary inverse-geometry digital tomosynthesis (s-IGDT) is able to reduce motion artifacts, image acquisition time and radiation dose, the image quality of the s-IGDT is degraded due to the truncations arisen in projections. Therefore, the effects of geometric and image acquisition conditions in the s-IGDT should be analyzed for improving the image quality and clinical applicability of the s-IGDT system. In this study, the s-IGDT images were obtained with the various X-ray source arrangement types and the various number of projections. The resolution and noise characteristics of the obtained s-IGDT images were evaluated, and the characteristics were compared with those of the conventional DT images. The s-IGDT system using linear X-ray source arrangement and 40 projections maximized the image characteristics of resolution and noise, and the corresponding system was superior to the conventional DT system in terms of image resolution. In conclusion, we expect that the s-IGDT system can be used for providing medical images in diagnosis.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1911-1923
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• 2022

The availability of high-resolution satellite images provides precise information without direct observation of the research target. Korea Multi-Purpose Satellite (KOMPSAT), also known as the Arirang satellite, has been developed and utilized for earth observation. The machine learning model was continuously proven as a good classifier in classifying remotely sensed images. This study aimed to compare the performance of the support vector machine (SVM) model in classifying the land cover of the Delaware River port area on high and medium-resolution images. Three optical images, which are KOMPSAT-2, KOMPSAT-3A, and Sentinel-2B, were classified into six land cover classes, including water, road, vegetation, building, vacant, and shadow. The KOMPSAT images are provided by Korea Aerospace Research Institute (KARI), and the Sentinel-2B image was provided by the European Space Agency (ESA). The training samples were manually digitized for each land cover class and considered the reference image. The predicted images were compared to the actual data to obtain the accuracy assessment using a confusion matrix analysis. In addition, the time-consuming training and classifying were recorded to evaluate the model performance. The results showed that the KOMPSAT-3A image has the highest overall accuracy and followed by KOMPSAT-2 and Sentinel-2B results. On the contrary, the model took a long time to classify the higher-resolution image compared to the lower resolution. For that reason, we can conclude that the SVM model performed better in the higher resolution image with the consequence of the longer time-consuming training and classifying data. Thus, this finding might provide consideration for related researchers when selecting satellite imagery for effective and accurate image classification.

• Electronics and Telecommunications Trends
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• v.35 no.4
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• pp.91-102
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• 2020

Recently, generative adversarial networks (GANs) is a field of research that has rapidly emerged wherein many studies conducted shows overwhelming results. Initially, this was at the level of imitating the training dataset. However, the GAN is currently useful in many fields, such as transformation of data categories, restoration of erased parts of images, copying facial expressions of humans, and creation of artworks depicting a dead painter's style. Although many outstanding research achievements have been attracting attention recently, GANs have encountered many challenges. First, they require a large memory facility for research. Second, there are still technical limitations in processing high-resolution images over 4K. Third, many GAN learning methods have a problem of instability in the training stage. However, recent research results show images that are difficult to distinguish whether they are real or fake, even with the naked eye, and the resolution of 4K and above is being developed. With the increase in image quality and resolution, many applications in the field of design and image and video editing are now available, including those that draw a photorealistic image as a simple sketch or easily modify unnecessary parts of an image or a video. In this paper, we discuss how GANs started, including the base architecture and latest technologies of GANs used in high-resolution, high-quality image creation, image and video editing, style translation, content transfer, and technology.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.49-52
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• 2002

High-resolution satellite image processing software should be able to ensure accurate, fast, compact data processing in offline or online environment. In this paper, component software for high-resolution satellite image processing is developed using OpenGIS components and real-time data processing architecture. The developed component software is composed of three major packages, which are data provide package, user interface package, and fast data processing package. The data provider package encodes and decodes diverse image/vector data formats and give identical data access methods to developers. The user interface package supports menus, toolbars, dialogs, and events to use easier. The fast data processing package follows the OpenGIS's data processing standards, which can deal with several processors as components with standard procedural functionalities.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.113-117
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• 2020

Images were taken under various weather such as rain, haze, snow often show low visibility, which can dramatically decrease accuracy of some tasks in computer vision: object detection, segmentation. Besides, previous work to enhance image usually downsample the image to receive consistency features but have not yet good upsample algorithm to recover original size. So, in this research, we jointly implement removal streak in heavy rain image and super resolution using a deep network. We put forth a 2-stage network: a multi-model network followed by a refinement network. The first stage using rain formula in the single image and two operation layers (addition, multiplication) removes rain streak and noise to get clean image in low resolution. The second stage uses refinement network to recover damaged background information as well as upsample, and receive high resolution image. Our method improves visual quality image, gains accuracy in human action recognition task in datasets. Extensive experiments show that our network outperforms the state of the art (SoTA) methods.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.344-353
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• 2012

In this paper, we propose a super-resolution algorithm using discrete wavelet transform. In general super-resolution algorithms for single-image, probability based operations have been used for searching high-frequency components. Consequently, the complexity of the algorithm causes the increase of processing time. In the proposed algorithm, we use discrete wavelet transform to find high-frequency sub-bands. We perform inverse discrete wavelet transform using input image and high-frequency sub-bands of the same resolution as the input image which are obtained by performing discrete wavelet transform without down-sampling and then we obtain image with high-resolution. In the proposed algorithm, we use the down-sampled version of the original image ($512{\times}512$) as a test image ($256{\times}256$) to compare the performance of algorithms. Through experimental results, we confirm the improved efficiency of the proposed algorithm comparing with conventional interpolation algorithms and also decreased processing time comparing the probability based operations.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.45-56
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• 2001

To acquire seabed information, the mosaic images of the seabed were generated using Side Scan Sonar. Short time energy function which is needed for slant range correction is proposed to get the height of Tow-Fish to the reflected acoustic amplitudes of each ping, and that leads to a mosaic image without water column. While generating mosaic image, maximum value, last value and average value are used for the measure of a pixel in the mosaic image and 3-D information was kept by using acoustic amplitudes which were heading for specific direction. As a generating method of mosaic image, low resolution mosaic image which is over 1m/pixel resolution was generated for whole survey area first, and then high resolution mosaic image which is generated under 0.1m/pixel resolution was generated for the selected area. Rocks, ripple mark, sand wave, tidal flat and artificial fish reef are found in the mosaic image.

• Journal of Space Technology and Applications
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• v.1 no.1
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• pp.41-48
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• 2021

In this paper, we will discuss techniques that can increase the resolution by 1.4 times without distortion or performance degradation of the original image, using diagonal information of the image. The applied method is to use the image information of 4 adjacent points without actual rotating the image by 45 degrees and enlarge and rearrange it according to the characteristics of the camera, so that the same physical concept as the actual 45 degrees can be applied. This is a concrete realization method that can improve the resolution by 1.4 times without deterioration of performance and a demonstration of this result.