• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.205-207
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• 2020

This paper proposes a novel deep learning-based method to upsample a depth map. Most conventional methods estimate high-resolution depth map by modifying pixel value of given depth map using high-resolution color image and low-resolution depth map. However, these methods cause under- or over-shooting problems that restrict performance improvement. To overcome these problems, the proposed method iteratively performs grid warping scheme which shifts pixel values to restore blurred image for estimating high-resolution depth map. Experimental results show that the proposed method improves both quantitative and visual quality compared to the existing method.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.39-45
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• 2017

In this paper, we propose three compensation methods to solve problems in high-resolution airborne infrared camera and to improve long-range target information acquisition performance. First, image motion and temporal noise reduction technique which is caused by atmospheric turbulence. Second, thermal blurring image correction technique by imperfect performance of NUC(Non Uniformity Correction) or raising the internal temperature of the camera. Finally, DRC(Dynamic Range Compression) and flicker removing technique of 14bits HDR(High Dynamic Range) infrared image. Through this study, we designed techniques to improve the acquisition performance of long-range target information of high-resolution airborne infrared camera, and compared and analyzed the performance improvement result with implemented images.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.559-564
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• 2002

This paper describes a new algorithm named as ray following algorithm which is applied for high-resolution satellite image simulation. The problems of the conventional ray tracing algorithm are pointed out especially when terrain elevations vary abruptly. The proposed algorithm follows the directional ray vector sequentially and thoroughly in order to determine the crossing point of the ray with the terrain surface. This way of sequential height comparison method is regarded as the only way to obtain accurate surface cross-section when a highly variant digital surface model is used. The experimental results show and compare the validities of the conventional and proposed algorithms.

• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1391-1401
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• 2019

The KOMPSAT-3A is a high-resolution optical satellite launched in 2015 by Korea Aerospace Research Institute (KARI). KOMPSAT-3A provides Panchromatic (PAN-0.55 m), Multispectral (MS-2.2 m), and Mid-wavelength infrared (MIR_OR-5.5 m) image. However, due to security or military problems, MIR_OR image with 5.5m spatial resolution are provided down sampled at 33 m spatial resolution (MIR_rd). In this study, we propose spatial sharpening method to improve the spatial resolution of MIR_rd image (33 m) using virtual High Frequency (HF) image and optimal fusion factor. Using MS image and MIR_rd image, we generated virtual high resolution (5.5 m) MIR_OR^fus image and then compared them to actual high-resolution MIR_OR image. The test results show that the proposed method merges the spatial resolution of MS image and the spectral information of MIR_rd image efficiently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.5
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• pp.952-958
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• 2009

Recently, due to problems in terms of illegal copying of medical image and the right ownership and authentication of data, it is necessary for us to study about those problems. In this study, we propose steganography with a method of the hiding information of high-resolution in digital medical image. The proposed algorithm is one of the way that inserts secret information by protecting ROI area which is regarded as and important feature of high-resolution digital medical image. As a result, the proposed method made it possible to insert secret information of massive storage and didn't affect the imperceptibility in medical image quality based on capacity and PSNR showed the all image quality of about 33.33dB.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.5
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• pp.775-784
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• 2023

Drone images are being used more and more actively in the fields of surveying and spatial information, and are rapidly replacing existing aerial and satellite images. The technology of quickly acquiring real-time data at low cost and processing it is now being applied to actual industries beyond research. However, there are also problems encountered as this progresses. When high-resolution spatial information is acquired using a general 2D flight plan for a terrain with sever undulations, problems arise due to the difference in resolution of the data. In particular, when a low-altitude high-resolution image is taken using a drone in a mountainous or steep terrain, there may be a problem in image matching due to a resolution difference caused by terrain undulations. This problem occurs because a drone acquires data while flying on a 2D plane at a fixed altitude, just like conventional aerial photography. In order to acquire high-quality 3D data using a drone, the scale difference for the shooting distance should be considered. In addition, in order to obtain facade images of large structures, it is necessary to take images in 3D space. In this study, in order to improve the disadvantages of the 2D flight method, a 3D flight plan was established for the study area, and it was confirmed that high-quality 3D spatial information could be obtained in this way.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.45-50
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• 2010

An image interpolation is a technique to use for enhancement of image resolution, it have two problems which are image quality degradation of the interpolated result image and high computation complexity. In this paper, to solve the problem, we propose an image interpolation algorithm using loss information estimation and implement the proposed method on portable device. From reduction image of obtained low resolution image, the proposed method can computes error to use image interpolated and estimate loss information by interpolation of the computed error. The estimated loss information is added to interpolated high resolution image with weight factor. We verified that the proposed method has improved FSNR as 2dB than conventional algorithms by experiments. Also, we implemented the proposed method on portable device and checked up real-time action. The proposed algorithm may be helpful for various application for image enlargement and reconstruction.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.19-27
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• 2020

In this study, Developing high resolution camera and Social Network Service sharing image can be easily getting images, it cause about taking fingerprints to easy from images. So I present solution about prevent to taking fingerprints. this technology is develop python using to opencv, blur libraries. First of all 'Hand Key point Detection' algorithm is used to locate the hand in the image. Using this algorithm can be find finger joints that can be protected while minimizing damage in the original image by using the coordinates of separate blurring the area of fingerprints in the image. from now on the development of accurate finger tracking algorithms, fingerprints will be protected by using technology as an internal option for smartphone camera apps from high resolution images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.5129-5152
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• 2016

Multi-view super-resolution (MVSR) aims to estimate a high-resolution (HR) image from a set of low-resolution (LR) images that are captured from different viewpoints (typically by different cameras). MVSR is usually applied in camera array imaging. Given that MVSR is an ill-posed problem and is typically computationally costly, we super-resolve multi-view LR images of the original scene via image fusion (IF) and blind deblurring (BD). First, we reformulate the MVSR problem into two easier problems: an IF problem and a BD problem. We further solve the IF problem on the premise of calculating the depth map of the desired image ahead, and then solve the BD problem, in which the optimization problems with respect to the desired image and with respect to the unknown blur are efficiently addressed by the alternating direction method of multipliers (ADMM). Our approach bridges the gap between MVSR and BD, taking advantages of existing BD methods to address MVSR. Thus, this approach is appropriate for camera array imaging because the blur kernel is typically unknown in practice. Corresponding experimental results using real and synthetic images demonstrate the effectiveness of the proposed method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.121-132
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• 2016

This study proposes an approach for simulating high spatial resolution satellite images acquired under arbitrary sun-sensor geometry using existing images and 3D (three-dimensional) data. First, satellite images, having significant differences in spectral regions compared with those in the simulated image were transformed to the same spectral regions as those in simulated image by using the UPDM (Universal Pattern Decomposition Method). Simultaneously, shadows cast by buildings or high features under the new sun position were modeled. Then, pixels that changed from shadow into non-shadow areas and vice versa were simulated on the basis of existing images. Finally, buildings that were viewed under the new sensor position were modeled on the basis of open library-based 3D reconstruction program. An experiment was conducted to simulate WV-3 (WorldView-3) images acquired under two different sun-sensor geometries based on a Pleiades 1A image, an additional WV-3 image, a Landsat image, and 3D building models. The results show that the shapes of the buildings were modeled effectively, although some problems were noted in the simulation of pixels changing from shadows cast by buildings into non-shadow. Additionally, the mean reflectance of the simulated image was quite similar to that of actual images in vegetation and water areas. However, significant gaps between the mean reflectance of simulated and actual images in soil and road areas were noted, which could be attributed to differences in the moisture content.