• Journal of the Korea Institute of Military Science and Technology
• /
• v.25 no.5
• /
• pp.476-486
• /
• 2022

Synthetic dynamic infrared image generation from the given virtual environment is being the primary goal to simulate the output of the infra-red(IR) camera installed on a vehicle to evaluate the control algorithm for various search & reconnaissance missions. Due to the difficulty to obtain actual IR data in complex environments, Artificial intelligence(AI) has been used recently in the field of image data generation. In this paper, CycleGAN technique is applied to obtain a more realistic synthetic IR image. We added the Structural Similarity Index Measure(SSIM) loss function to the L1 loss function to generate a more realistic synthetic IR image when the CycleGAN image is generated. From the simulation, it is applicable to the guided-missile flight simulation tests by using the synthetic infrared image generated by the proposed technique.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.24 no.4
• /
• pp.459-465
• /
• 2013

This paper presents a differential interferometry technique for soil moisture change detection by measuring surface-height variation. COSMO-SkyMed SAR images were used to verify the DInSAR(differential interferometric SAR) technique. The soil penetration depth changes according to soil moisture, that causes phase change of the received signal. The height of soil surface and its displacement can be detected by a radar interferometry technique using phase difference of two received signals. To retrieve displacement variation, one of three SAR images is used as a reference image. Reference image and other two images are processed by the differential interferometry technique in the same area. The soil moisture was measured for the test sites to verify the DInSAR technique. The penetration depth is calculated by using the in-situ measured soil moisture data and it is compared with the displacement values acquired by the DInSAR technique.

• Journal of Broadcast Engineering
• /
• v.27 no.7
• /
• pp.999-1010
• /
• 2022

The increase in vehicle purchases worldwide is having a very significant impact on the availability of parking spaces. In particular, since it is difficult to secure a parking space in an urban area, it may be of great help to the driver to check vehicle parking information in advance. However, the current parking lot information is still operated semi-manually, such as notifications. Therefore, in this study, we propose a system for detecting a parking space using a relatively simple image processing method based on an image taken from the sky and evaluate its performance. The proposed method first converts the captured RGB image into a black-and-white binary image. This is to simplify the calculation for detection using discrete information. Next, a morphological operation is applied to increase the clarity of the binary image, and a template mask in the form of a bounding box indicating a parking space is applied to check the parking state. Twelve image samples and 2181 total of test, were used for the experiment, and a threshold of 40% was used to detect each parking space. The experimental results showed that information on the availability of parking spaces for parking users was provided with an accuracy of 95%. Although the number of experimental images is somewhat insufficient to address the generality of accuracy, it is possible to confirm the possibility of parking space detection with a simple image processing method.

• International Journal of Internet, Broadcasting and Communication
• /
• v.12 no.2
• /
• pp.21-29
• /
• 2020

This paper presents an effective single image haze removal using edge-preserving and adaptive transmission estimation to enhance the visibility of outdoor images vulnerable to weather and environmental conditions with computational complexity reduction. The conventional methods involve the time-consuming refinement process. The proposed transmission estimation however does not require the refinement, since it preserves the edges effectively, which selects one between the pixel-based dark channel and the patch-based dark channel in the vicinity of edges. Moreover, we propose an adaptive transmission estimation to improve the visual quality particularly in bright areas like sky. Experimental results with various hazy images represent that the proposed method is superior to the conventional methods in both subjective visual quality and computational complexity. The proposed method can be adopted to compose a haze removal module for realtime devices such as mobile devices, digital cameras, autonomous vehicles, and so on as well as PCs that have enough processing resources.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.378-381
• /
• 2002

We retrieved the aerosol optical thickness $\tau$$_{a}$ over land from Landsat-7/ETM+ image data using the correlation between the visible reflectance and middle IR reflectance. This band correlation method for aerosol retrieval was originally proposed fur MODIS data analysis by Kaufman et al.(1977). The results of retrieved aerosol optical thickness $\tau$$_{a}$ from Landsat-7/ETM+ data were compared with the simultaneous sky observation data at our study site. We found a good agreement between the retrieved and observed values. We presented the distribution maps of the aerosol optical thickness over land, retrieved from Landsat-7/ETM+ image data. Then, the surface reflectance map was also presented. The aerosol optical thickness over sea was retrieved assuming no reflected contribution from sea in the near IR band. In addition, we discussed some limitations when we apply the band correlation method.

• Journal of Astronomy and Space Sciences
• /
• v.28 no.4
• /
• pp.273-284
• /
• 2011

A method of stellar source selection for validating the quality of image is investigated for a low Earth orbit optical remote sensing satellite. Image performance of the optical payload needs to be validated after its launch into orbit. The stellar sources are ideal source points that can be used to validate the quality of optical images. For the image validation, stellar sources should be the brightest as possible in the charge-coupled device dynamic range. The time delayed and integration technique, which is used to observe the ground, is also performed to observe the selected stars. The relations between the incident radiance at aperture and V magnitude of a star are established using Gunn & Stryker's star catalogue of spectrum. Applying this result, an appropriate image performance index is determined, and suitable stars and areas of the sky scene are selected for the optical payload on a remote sensing satellite to observe. The result of this research can be utilized to validate the quality of optical payload of a satellite in orbit.

• The Research Journal of the Costume Culture
• /
• v.19 no.6
• /
• pp.1177-1192
• /
• 2011

As a free creature that can fly in the sky, the bird has been an object of admiration and mystery and a mediator between human beings and the heavens. This study aims to clarify the aesthetic value of birds through study of the various expressions of the bird image on clothing and by the formative will of designers. Based on the general examination of the bird image through the study of documents, this study is composed of a case analysis, which reveals on modern fashion designs. Additionally, the forms of expression of the bird image are organized according to the stereoscopic expression of shaping, the relief expression of handicraft decoration, the flat expression of surface design, and the characteristic expression of wings and feathers. The aesthetic characteristics revealed by the expression patterns are metaphorical symbolism, surrealistic humor, lyrical naturalness, and fantastical femininity. Since antiquity, the bird image continuously recreated by artists has offered aesthetic value in terms of formativeness in the external form and symbolism in the internal form. This study would help to understand the diversity of creation in contemporary fashion design.

• ETRI Journal
• /
• v.39 no.1
• /
• pp.97-107
• /
• 2017

A fast and accurate building-level visual place recognition method built on an image-retrieval scheme using street-view images is proposed. Reference images generated from street-view images usually depict multiple buildings and confusing regions, such as roads, sky, and vehicles, which degrades retrieval accuracy and causes matching ambiguity. The proposed practical database refinement method uses informative reference image and keypoint selection. For database refinement, the method uses a spatial layout of the buildings in the reference image, specifically a building-identification mask image, which is obtained from a prebuilt three-dimensional model of the site. A global-positioning-system-aware retrieval structure is incorporated in it. To evaluate the method, we constructed a dataset over an area of $0.26km^2$. It was comprised of 38,700 reference images and corresponding building-identification mask images. The proposed method removed 25% of the database images using informative reference image selection. It achieved 85.6% recall of the top five candidates in 1.25 s of full processing. The method thus achieved high accuracy at a low computational complexity.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.183-183
• /
• 2021

Deep learning methods and their application have become an essential part of prediction and modeling in water-related research areas, including hydrological processes, climate change, etc. It is known that application of deep learning leads to high availability of data sources in hydrology, which shows its usefulness in analysis of precipitation, runoff, groundwater level, evapotranspiration, and so on. However, there is still a limitation on microclimate analysis and prediction with deep learning methods because of deficiency of gauge-based data and shortcomings of existing technologies. In this study, a real-time rainfall prediction model was developed from a sky image data set with convolutional neural networks (CNNs). These daily image data were collected at Chung-Ang University and Korea University. For high accuracy of the proposed model, it considers data classification, image processing, ratio adjustment of no-rain data. Rainfall prediction data were compared with minutely rainfall data at rain gauge stations close to image sensors. It indicates that the proposed model could offer an interpolation of current rainfall observation system and have large potential to fill an observation gap. Information from small-scaled areas leads to advance in accurate weather forecasting and hydrological modeling at a micro scale.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2001.10a
• /
• pp.95-98
• /
• 2001

Edge detection is an important problem in computer vision and image understanding. Because the threshold is difficult to properly determine, edge images gained by the usually gradient-based segmentation methods are often tend to have many disjoint or overlapping boundaries, which makes the edge images spinous. In this paper, a practical multilevel morphological filter is presented for smoothing spinous edge images. The experimental results show that the method is effective in dealing with the images of a target in the sky.