• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1814-1828
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• 2021

Low-light image enhancement is a key technique to overcome the quality degradation of photos taken under scotopic vision illumination conditions. The degradation includes low brightness, low contrast, and outstanding noise, which would seriously affect the vision of the human eye recognition ability and subsequent image processing. In this paper, we propose an approach based on deep learning and Retinex theory to enhance the low-light image, which includes image decomposition, illumination prediction, image reconstruction, and image optimization. The first three parts can reconstruct the enhanced image that suffers from low-resolution. To reduce the noise of the enhanced image and improve the image quality, a super-resolution algorithm based on the Laplacian pyramid network is introduced to optimize the image. The Laplacian pyramid network can improve the resolution of the enhanced image through multiple feature extraction and deconvolution operations. Furthermore, a combination loss function is explored in the network training stage to improve the efficiency of the algorithm. Extensive experiments and comprehensive evaluations demonstrate the strength of the proposed method, the result is closer to the real-world scene in lightness, color, and details. Besides, experiments also demonstrate that the proposed method with the single low-light image can achieve the same effect as multi-exposure image fusion algorithm and no ghost is introduced.

• Korean Security Journal
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• no.61
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• pp.163-179
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• 2019

The purpose of this study is to analyze the effect of service quality of security safety system users on corporate image and customer satisfaction. To confirm this through empirical analysis, a survey was conducted on about 200 users nationwide for about 40 days from May 2 to June 12, 2019. The survey was composed of "service quality, corporate image and customer satisfaction". The empirical analysis was conducted mainly on the analysis of importance, reliability, validity and correlation. This study used SPSS WIN 18.0 to calculate structural equations and exploratory factors. The research results are as follows: The users of the security safety system showed that the better the service quality, the better the corporate image. The better the corporate image, the higher the customer satisfaction. Also, the better the service quality, the higher the customer satisfaction. Therefore, each security safety system company should steadily improve the service quality to improve customer satisfaction.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.145-153
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• 2019

The purpose of this study is to identify the effects of educational service quality on student satisfaction, university image, commitment, and loyalty in the changing environment of university education environment, and to suggest a strategic plan for university education in high quality. To do this, we set up six hypotheses and conducted an empirical analysis with the sample of 229 senior students attending colleges and universities in the metropolitan area. The results of hypothesis verification says that the educational service quality has a positive effect on satisfaction and image, and the satisfaction shows an influence on commitment and loyalty. But the image proved to have no effect on commitment. The commitment was found to affect loyalty. It can be said that the efforts to improve the quality of educational service have an impact on the image and loyalty of colleges and universities and the effects help to improve the long term competitiveness of colleges and universities. The ultimate effects for the quality control of educational service will suggest the survival ways in the changing university educational environment.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1701-1704
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• 2003

In this paper, we proposed an watermarking algorithm in which invariable sign of DWT coefficients should be used and by which the quality of digital image can be preserved for the protection of copyright. According to the algorithm, through the calculation of the sign DWT coefficients and the use of elements, position of watermark and size value should be decided. By so doing, the algorithm can improve image quality(PSNR) and obtain good efficiency with which strong watermark can be inserted into the digital image.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.597-600
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• 1999

TMN5 used to test the performance of H.263 is a DCT-based H.263 which DCT is used as transform coding, but DWT is used instead of DCT and adaptive quantizer of being appropriate to DWT is designed in this paper while the structure of TMN5 is maintained. DWT-based H.263, which is proposed in this paper, is excellent in transplantation of the existing system and can improve frame rate by transmitting more Frame. Also, the average PSNR, objective quality of image, has been lost at degree of average 0.35㏈ in luminance signals, but has been improved over a average of 2㏈ in chrominance signals. Subjective quality of image has been improved as blocking effect, which has seriously occurred in DCT based H.263, is diminished. DWT-based H.263 can. therefore. advance video quality of image comparing with the existing ways.

• Journal of radiological science and technology
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• v.42 no.2
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• pp.119-130
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• 2019

Positron emission tomography (PET) is widely used imaging modality for effective and accurate functional testing and medical diagnosis using radioactive isotopes. However, PET has difficulties in acquiring images with high image quality due to constraints such as the amount of radioactive isotopes injected into the patient, the detection time, the characteristics of the detector, and the patient's motion. In order to overcome this problem, we have succeeded to improve the image quality by using the dynamic image reconstruction method based on singular value decomposition. However, there is still some question about the characteristics of the proposed technique. In this study, the characteristics of reconstruction method based on singular value decomposition was estimated over computational simulation. As a result, we confirmed that the singular value decomposition based reconstruction technique distinguishes the images well when the signal - to - noise ratio of the input image is more than 20 decibels and the feature vector angle is more than 60 degrees. In addition, the proposed methode to estimate the characteristics of reconstruction technique can be applied to other spatio-temporal feature based dynamic image reconstruction techniques. The deduced conclusion of this study can be useful guideline to apply medical image into SVD based dynamic image reconstruction technique to improve the accuracy of medical diagnosis.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.7-13
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• 2021

Machine vision is a technology that helps the computer as if a person recognizes and determines things. In recent years, as advanced technologies such as optical systems, artificial intelligence and big data advanced in conventional machine vision system became more accurate quality inspection and it increases the manufacturing efficiency. In machine vision systems using deep learning, the image quality of the input image is very important. However, most images obtained in the industrial field for quality inspection typically contain noise. This noise is a major factor in the performance of the machine vision system. Therefore, in order to improve the performance of the machine vision system, it is necessary to eliminate the noise of the image. There are lots of research being done to remove noise from the image. In this paper, we propose an autoencoder based machine vision system to eliminate noise in the image. Through experiment proposed model showed better performance compared to the basic autoencoder model in denoising and image reconstruction capability for MNIST and fashion MNIST data sets.

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.233-238
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• 2010

In this paper, we propose a multiple classifier combination method based on image degradation modeling to improve recognition performance on low-quality images. Using an image degradation model, it generates a set of classifiers each of which is specialized for a specific image quality. In recognition, it combines the results of the recognizers by weighted averaging to decide the final result. At this time, the weight of each recognizer is dynamically decided from the estimated quality of the input image. It assigns large weight to the recognizer specialized to the estimated quality of the input image, but small weight to other recognizers. As the result, it can effectively adapt to image quality variation. Moreover, being a multiple-classifier system, it shows more reliable performance then the single-classifier system on low-quality images. In the experiment, the proposed multiple-classifier combination method achieved higher recognition rate than multiple-classifier combination systems not considering the image quality or single classifier systems considering the image quality.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.4
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• pp.447-452
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• 1988

This paper proposes a hybrid image coding in order to improve the coding performance by combining the BTC with the DPCM. And utilizing the human perceptual characteristics, a new objective image quality evaluation method has been proposed to obtain an excellent result in good agreement with the subjective quality evaluation. A hyb-1 method consisting of the DPCM and the AMBTC has retained a good picture quality at the bit rate of 1.5 bits/pel. A hyb-3 method combining the EBTC-3 with the DPCM has scarcely degraded the picture quality compared with the original image at the bit rate of 2.1 bits/pel. A newly proposed mehtod of picture quality evaluation accumulating a blocky noise at the edge block and an impulsive noise at the flat block selectively has been coincident with the subjective evaluation of quality.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.13-16
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• 2001

In the Dedicated Short Range Communication (DSRC) system channel, a large number of bit errors occur because of Additive White Gaussian Noise (AWGN) and fading. When an image data is transmitted under the condition, reconstructed image quality is significantly degraded. In this paper, as an alternative to the error correcting code and/or automatic repeat request scheme, we propose an error recovery scheme for image data transmission. We first analyze how transmission errors in the DSRC system channel degrade image quality. Then, in order to improve image quality, we propose error resilient and concealment schemes for still image transmission using DCT-based fixed length coding, hamming code, cyclic redundancy check, and interleaver. Finally, we show its performance by an experiment.