• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.4
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• pp.213-219
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• 2017

Streaming server is that an image produced in real time or a file form of image produced ahead consists of SNS service, and the relay module of streaming server includes output management module that set an output channel more than 2 and control transmission of video content. This thesis intends to suggest how to stream through plural output channel that contains output channel of external streaming server using relay module and do streaming provided to terminal receiving image, and streaming server, streaming system for this. Thus, by extending output channel sending out image to output channel of external streaming server, the scale of streaming server is not limited and the process allotting external streaming server into output channel sending the image becomes simple, so management of output channel becomes efficient even when sending several images.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.110-113
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• 2003

In this paper, the multi-channel high speed data acquisition system is implemented. This high speed signal processing system for 3-D image display is applicable to the manipulation of a medical image processing, multimedia data and various fields of digital image processing. In order to convert the analog signal into digital one, A/D conversion circuit is designed. PCI interface method is designed and implemented, which is capable of transmission a large amount of data to computer. In order to, especially, channel extendibility of images acquisition, bus communication method is selected. By using this bus method, we can interface each module effectively. In this paper, 32-channel A/D conversion and PCI interface system for 3-dimensional and real-time display of the retina image is developed. The 32-channel image acquisition system and high speed data transmission system developed in this paper is applicable to not only medical image processing as 3-D representation of retina image but also various fields of industrial image processing in which the multi-point realtime image acquisition system is needed.

• Journal of Internet Computing and Services
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• v.6 no.5
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• pp.133-141
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• 2005

In this paper, we designed about OFDM/QPSK image transmission system simulator embedded watermark in wireless channel environment. Channel environment used OFDM/QPSK still image transmission system considering AWGN, Multi-path fading. And, we analyzed effect of still image and watermark information in considered channel environment. Watermark information is coded by DM-SS (Direct Matric/Spread Spectrum) image watermarking scheme, Also, we used interleaving scheme for mitigating the degradation in watermarking data under wireless channel. As a results, we could know that PSNR of watermark image improved of about 1dB by 54.2371dB then apply interleaving in same multi-path fading environment.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.42.3-42.3
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• 2019

We translate Solar Dynamics Observatory/Atmospheric Imaging Assembly (AIA) ultraviolet (UV) multi-channel images into another UV single-channel image using a deep learning algorithm based on conditional generative adversarial networks (cGANs). The base input channel, which has the highest correlation coefficient (CC) between UV channels of AIA, is 193 Å. To complement this channel, we choose two channels, 1600 and 304 Å, which represent upper photosphere and chromosphere, respectively. Input channels for three models are single (193 Å), dual (193+1600 Å), and triple (193+1600+304 Å), respectively. Quantitative comparisons are made for test data sets. Main results from this study are as follows. First, the single model successfully produce other coronal channel images but less successful for chromospheric channel (304 Å) and much less successful for two photospheric channels (1600 and 1700 Å). Second, the dual model shows a noticeable improvement of the CC between the model outputs and Ground truths for 1700 Å. Third, the triple model can generate all other channel images with relatively high CCs larger than 0.89. Our results show a possibility that if three channels from photosphere, chromosphere, and corona are selected, other multi-channel images could be generated by deep learning. We expect that this investigation will be a complementary tool to choose a few UV channels for future solar small and/or deep space missions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.545-551
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• 2012

In this paper, K-band multi-channel receiver was designed and fabricated for low noise amplification and down conversion to L-band. The fabricated multi-channel receiver incorporates GaAs-HEMT LNA(Low noise amplifier) which provides less than a 2 dB noise figure, IR(Image Rejection) Filter for rejection of image frequency, IR(Image rejection) mixer to reject a image frequency and improve an IMD(Intermodulation Distortion) characteristic. Test results of the fabricated multi-channel receiver show less than a 3.8 dB noise figure, conversion gain of more than 27dB, and IP1dB(Input 1dB Gain Compression Point) of -9.5 dB and over.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.165-170
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• 2015

The unsharp mask technique emphasize the boundary of the image by adding the boundary of the original image. This technique improves quality by emphasize its boundaries but produce rough image from image noise. The multi channel unsharp mask is possible to enhance entire contrast of the image by applying at least two channels of unsharp mask. However, There is limitations to strengthen boundaries even if the scale strongly applies the multi channel unsharp mask technique. To solve this problem, linear scaling to nonlinear scaling by applying exponential function to existing multi channel unsharp mask technique. Experimental results show enhanced contrast for desired area because of control scaling in details compared with existing unsharp mask technique.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1513-1517
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• 2005

In this paper, I make use of a Multi-Channel skin color model with Hue, Cb, Cg using Red, Blue, Green channel altogether which remove bight component as being consider the characteristics of skin color to do modeling more effective to a facial skin color for extracting a facial area. 1 used efficient HOLA(Higher order local autocorrelation function) using 26 feature vectors to obtain both feature vectors of a facial area and the edge image extraction using Harr wavelet in image which split a facial area. Calculated feature vectors are used of date for the facial recognition through learning of neural network It demonstrate improvement in both the recognition rate and speed by proposed algorithm through simulation.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.530-532
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• 2007

Multi-Spectral Camera(MSC) is a main payload on the KOMPSAT-2 satellite to perform the earth remote sensing. The MSC instrument has one(1) channel for panchromatic imaging and four(4) channel for multi-spectral imaging covering the spectral range from 450nm to 900nm using TDI CCD Focal Plane Array (FPA). The compression method on KOMPSAT-2 MSC was selected and used to match EOS input rate and PDTS output data rate on MSC image data chain. At once the MSC performance was carefully handled to minimize any degradation so that it was analyzed and restored in KGS(KOMPSAT Ground Station) during LEOP and Cal./Val.(Calibration and Validation) phase. In this paper, on-orbit image data chain in MSC and image data processing on KGS including general MSC description is briefly described. The influences on image performance between on-board compression algorithms and between performance restoration methods in ground station are analyzed and discussed.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.427-438
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• 2023

Plenty of works have indicated that single image super-resolution (SISR) models relying on synthetic datasets are difficult to be applied to real scene text image super-resolution (STISR) for its more complex degradation. The up-to-date dataset for realistic STISR is called TextZoom, while the current methods trained on this dataset have not considered the effect of multi-scale features of text images. In this paper, a multi-scale and attention fusion model for realistic STISR is proposed. The multi-scale learning mechanism is introduced to acquire sophisticated feature representations of text images; The spatial and channel attentions are introduced to capture the local information and inter-channel interaction information of text images; At last, this paper designs a multi-scale residual attention module by skillfully fusing multi-scale learning and attention mechanisms. The experiments on TextZoom demonstrate that the model proposed increases scene text recognition's (ASTER) average recognition accuracy by 1.2% compared to text super-resolution network.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.363-365
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• 2003

This paper presents an object oriented approach(OOA) for classification of multi-channel and multi-polarization NASA/JPL POLSAR images. Some test results in Taiwan are also given and analyzed. It is concluded that this approach can utilize as more information of both low- and high-levels involved in all images as possible for image classification and thus provides a better classification accuracy. For instance, the OOA has a better overall classification accuracy(98.27%) than the nearest-neighbor classifier(91.31%) and minimum-distance classifier(80.52%).