• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.145-148
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• 2007

The Korea Multi-Purpose Satellite-2 (KOMPSAT-2) was launched in July 2006 and The main mission of the KOMPSAT-2 is a high resolution imaging for the cartography of Korea peninsula by utilizing Multi Spectral Camera (MSC) images. The camera resolutions are 1 m in panchromatic scene and 4 m in multi-spectral imaging. KOMPSAT-2 measure the position, velocity and attitude data of satellite using by star sensor, gyro sensor, and GPS sensor. This paper provides an initial geometric accuracy assessment of the KOMPSAT-2 high resolution image, both geometric Cal/Val overview.

• Journal of electromagnetic engineering and science
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• v.2 no.1
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• pp.39-44
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• 2002

A high speed data link capability is one of the critical factors in determining the performance of the spaceborne SAR system with high resolution because of the strict requirement far the real-time data transmission of the massive SAR data in a limited time of mission. In this paper, based on the data lint model characterized by the spaceborne small SAR system, the high rate multi-channel data link module is designed including link storage, link processor, transmitter, and wide-angle antenna. The design results are presented with the performance analysis on the data link budget as well as the multi-mode data rate in association with the SAR imaging mode of operation from high resolution to the wide swath.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.807-810
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• 2000

In this paper, a new hierarchical motion estimation (ME) scheme using the wavelet transformed multi-resolution image layers is proposed. While the coarse-to-fine (CtF) ME, used in previously proposed coding schemes, can provide a better estimate at the coarsest resolution, it is difficult to accurately track motion at finer resolution. On the other hand, in fine-to-coarse (FtC) ME, it can solves this local minima problem by estimating motion track at the finest subband and propagating the motion vector (MV) to coarser subband. But this method causes to higher computational overhead. This paper proposes a new method for reducing the computational overhead of fine-to-coarse rnulti-resolution motion estimation (MRME) at the finest resolution level by searching for the region to consider motion vectors of the coarsest resolution subband.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.390-395
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• 1999

Ocean Scanning Multispectral Imager (OSMI) is a payload on the Korean Multi-purpose SATellite (KOMPSAT) to perform worldwide ocean color monitoring for the study of biological oceanography KOMPSAT will be launched in the middle of November this year. The radiometric performance of OSMI is analyzed for various gain settings in the viewpoint of the instrument developer for OSMI calibration and application based on its ground performance measurement data for 8 primary spectral bands of OSMI. The radiometric response linearity and dynamic range are analyzed for the image radiometric calibration and the estimation of OSMI image quality for the ocean remote sensing area. The dynamic range is compared with the nominal input radiance for the ocean and the land. The noise equivalent radiance (NER) corresponding to the instrument radiometric noise is compared with the radiometric resolution of signal digitization (1-count equivalent radiance). The best gain setting of OSMI for ocean monitoring is recommended. This analysis is considered to be useful for the OSMI mission and operation planning, the OSMI image data calibration, and users' understanding about OSMI image quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4060-4079
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• 2020

Blur is an important type of image distortion. How to evaluate the quality of blurred image accurately and efficiently is a research hotspot in the field of image processing in recent years. Inspired by the multi-scale perceptual characteristics of the human visual system (HVS), this paper presents a no-reference image blur/sharpness assessment method based on multi-scale local features in the spatial domain. First, considering various content has different sensitivity to blur distortion, the image is divided into smooth, edge, and texture regions in blocks. Then, the Gaussian scale space of the image is constructed, and the categorized contrast features between the original image and the Gaussian scale space images are calculated to express the blur degree of different image contents. To simulate the impact of viewing distance on blur distortion, the distribution characteristics of local maximum gradient of multi-resolution images were also calculated in the spatial domain. Finally, the image blur assessment model is obtained by fusing all features and learning the mapping from features to quality scores by support vector regression (SVR). Performance of the proposed method is evaluated on four synthetically blurred databases and one real blurred database. The experimental results demonstrate that our method can produce quality scores more consistent with subjective evaluations than other methods, especially for real burred images.

• Imaging Science in Dentistry
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• v.40 no.1
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• pp.15-23
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• 2010

Purpose : This study was designed to compare the effective doses from low-dose and standard-dose multi-detector CT (MDCT) scanning protocols and evaluate the image quality and the spatial resolution of the low-dose MDCT protocols for clinical use. Materials and Methods : 6-channel MDCT scanner (Siemens Medical System, Forschheim, Germany), was used for this study. Protocol of the standard-dose MDCT for the orthodontic analysis was 130 kV, 35 mAs, 1.25 mm slice width, 0.8 pitch. Those of the low-dose MDCT for orthodontic analysis and orthodontic surgery were 110 kV, 30 mAs, 1.25 mm slice width, 0.85 pitch and 110 kV, 45 mAs, 2.5 mm slice width, 0.85 pitch. Thermoluminescent dosimeters (TLDs) were placed at 31 sites throughout the levels of adult female ART head and neck phantom. Effective doses were calculated according to ICRP 1990 and 2007 recommendations. A formalin-fixed cadaver and AAPM CT performance phantom were scanned for the evaluation of subjective image quality and spatial resolution. Results : Effective doses in ${\mu}Sv$ ($E_{2007}$) were 699.1, 429.4 and 603.1 for standard-dose CT of orthodontic treatment, low-dose CT of orthodontic analysis, and low-dose CT of orthodontic surgery, respectively. The image quality from the low-dose protocol were not worse than those from the standard-dose protocol. The spatial resolutions of both standard-dose and low-dose CT images were acceptable. Conclusion : From the above results, it can be concluded that the low-dose MDCT protocol is preferable in obtaining CT images for orthodontic analysis and orthodontic surgery.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.898-910
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• 2020

Single image-based super-resolution has been studied for a long time in computer vision because of various applications. Various deep learning-based super-resolution algorithms are introduced recently to improve the performance by reducing side effects like blurring and staircase effects. Most deep learning-based approaches have focused on how to implement the network architecture, loss function, and training strategy to improve performance. Meanwhile, Several approaches using Attention Module, which emphasizes the extracted features, are introduced to enhance the performance of the network without any additional layer. Attention module emphasizes or scales the feature map for the purpose of the network from various perspectives. In this paper, we propose the various channel attention and spatial attention in single image-based super-resolution and analyze the results and performance according to the architecture of the attention module. Also, we explore that designing multi-attention module to emphasize features efficiently from various perspectives.

• Korean Journal of Optics and Photonics
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• v.23 no.4
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• pp.147-153
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• 2012

Multi-view 3D displays based on a limited number of pixels have the problem that the stereo-scopic image has a low resolution because of increasing view number. To solve the problem of low resolution, we propose an optical approaching method that focuses the width of a unit pixel by using a commercial spherical shape lenticular lens sheet and increases the effective resolution by increasing the number of sources of light in the multi-view 3D display system based on projection type. The method was performed in such an order that several main derivable parameters were defined, and, through the theoretical and experimental result, the value of the contractible unit pixel width and the scalable effective resolution was derived in a given system environment. As a result, for the case that the ray of light from the projector transmitted the 25 LPI lenticular lens sheet which has the pitch size 1.016 mm, the focused unit pixel width was 0.19 mm and the scalable effective resolution was, at most, 5 times wider than the original one. In addition, the range of depth of focus was 1.496 mm, which shows us the range of thickness tolerances of commercial spherical shape lenticular lens sheet and sufficient optical alignment tolerances.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.1
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• pp.41-49
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• 2023

A convolutional neural network (CNN) is a representative algorithm for implementing artificial neural networks. CNNs have improved on the issues of rapid increase in calculation amount and low object classification rates, which are associated with a conventional multi-layered fully-connected neural network (FNN). However, because of the rapid development of IT devices, the maximum resolution of images captured by current smartphone and tablet cameras has reached 108 million pixels (MP). Specifically, a traditional CNN algorithm requires a significant cost and time to learn and process simple, high-resolution images. Therefore, this study proposes an improved CNN algorithm for implementing an object classification learning model for simple, high-resolution images. The proposed method alters the adjacency matrix value of the pooling layer's max pooling operation for the CNN algorithm to reduce the high-resolution image learning model's creation time. This study implemented a learning model capable of processing 4, 8, and 12 MP high-resolution images for each altered matrix value. The performance evaluation result showed that the creation time of the learning model implemented with the proposed algorithm decreased by 36.26% for 12 MP images. Compared to the conventional model, the proposed learning model's object recognition accuracy and loss rate were less than 1%, which is within the acceptable error range. Practical verification is necessary through future studies by implementing a learning model with more varied image types and a larger amount of image data than those used in this study.

• Convergence Security Journal
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• v.7 no.1
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• pp.83-89
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• 2007

This paper is to suggest the method of embedding a signature to pictures secretly under the orthogonal wavelet transform which represents pictures as multi-resolution representations. As it is focused upon the differential output under the multi-resolution representation of pictures, this method can embed bit series to pictures. In doing so, it can compound approximately 6K byte of information with gray-level image $256{\times}256$. The method can include not only the database which designates copyright of pictures but also the author and usage of pictures, and the information of the picture itself. Therefore, this method can easily discriminate the inspection of picture database.