• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.60-66
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• 2019

In this paper, we propose a new free-view three-dimensional (3D) computational reconstruction of integral imaging to improve the visual quality of reconstructed 3D images when low-resolution elemental images are used. In a conventional free-view reconstruction, the visual quality of the reconstructed 3D images is insufficient to provide 3D information to applications because of the shift and sum process. In addition, its processing speed is slow. To solve these problems, our proposed method uses a pixel rearrangement technique (PERT) with locally selective elemental images. In general, PERT can reconstruct 3D images with a high visual quality at a fast processing speed. However, PERT cannot provide a free-view reconstruction. Therefore, using our proposed method, free-view reconstructed 3D images with high visual qualities can be generated when low-resolution elemental images are used. To show the feasibility of our proposed method, we applied it to optical experiments.

• Journal of Korean Society for Quality Management
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• v.44 no.3
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• pp.527-540
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• 2016

Purpose: The purpose of this study was to propose contrast metric which is based on the human visual perception and thus it can be used to improve the quality of digital images in many applications. Methods: Previous literatures are surveyed, and then the proposed method is modeled based on Human Visual System(HVS) such as multiscale property of the contrast sensitivity function (CSF), contrast constancy property (suprathreshold), color channel property. Furthermore, experiments using digital images are shown to prove the effectiveness of the method. Results: The results of this study are as follows; regarding the proposed contrast measure of complex images, it was found by experiments that HVS follows relatively well compared to the previous contrast measurement. Conclusion: This study shows the effectiveness on how to measure the contrast of complex images which follows human perception better than other methods.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.33-40
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• 2009

This paper proposes the assessment method for objective quality-evaluation-index of mosaic images. Quality assessment was evaluated using seam-line method and similarity and contrast of adjacent images. The evaluation measure was calculated based on selected evaluation criteria and compared with human visual inspection. It was found that quantitative quality evaluation measure showed that the evaluation results were similar to human visual check. Conclusively experimental results proved that proposed evaluation measure could be used for quantitative and objective quality assessment of mosaic images.

• Journal of Multimedia Information System
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• v.8 no.2
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• pp.93-100
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• 2021

Under the time-varying temperature, the high-temperature radiation of forgings and the change of reflection characteristics of oxide skin on the surface of forgings lead to the difficulty of obtaining images to truly reflect the geometric characteristics of forgings. It is urgent to study the clear and reliable acquisition method of hot forging feature image under time-varying temperature to meet the requirements of visual measurement of hot geometric parameters of forgings. Based on this, this chapter first puts forward the quality evaluation method of forging feature image, which provides guarantee for the accurate evaluation of feature image quality. Furthermore, the factors that affect the image quality, such as the radiation characteristics of forgings and the photographic characteristics of cameras, are analyzed, and the imaging spectrum which can effectively suppress the radiation intensity of forgings is determined. Finally, aiming at the problem that the quality of image acquisition is difficult to guarantee due to the drastic change of radiation intensity of forgings under time-varying temperature, an image acquisition method based on minimum signal-to-noise ratio (SNR) based laser light intensity adaptation is proposed, which significantly improves the definition of feature light strips in forging images at high temperature, and finally realizes the clear acquisition of feature images of large-scale hot forging under time-varying temperature.

• Smart Media Journal
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• v.8 no.4
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• pp.64-71
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• 2019

The performance of an OMR (Optical Music Recognition) system is usually determined by the characterizing features of the input music score images. Low resolution is one of the main factors leading to degraded image quality. In this paper, we handle the low-resolution problem using the super-resolution technique. We propose the use of a deep neural network with instance normalization to improve the quality of music score images. We apply instance normalization which has proven to be beneficial in single image enhancement. It works better than batch normalization, which shows the effectiveness of shifting the mean and variance of deep features at the instance level. The proposed method provides an end-to-end mapping technique between the high and low-resolution images respectively. New images are then created, in which the resolution is four times higher than the resolution of the original images. Our model has been evaluated with the dataset "DeepScores" and shows that it outperforms other existing methods.

• Journal of Korea Multimedia Society
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• v.17 no.10
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• pp.1205-1212
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• 2014

In this paper, we propose a high-quality stitching method of 3D multiple dental CT images. First, a weighted function is generated using the difference of two distance functions that calculate a distance from the nearest edge of an overlapped region to each position. And a blending ratio propagation function for two gradient vectors is parameterized by the difference and magnitude of gradient vectors that is also applied by the weighted function. When the blending ratio is propagated, an improved region growing scheme is proposed to decide the next position and calculate the blending intensity. The proposed method produces a high-quality stitching image. Our method removes the seam artifact caused by the mean intensity difference between images and vignetting effect. And it removes double edges caused by local misalignment. Experimental results showed that the proposed method produced high-quality stitching images for ten patients. Our stitching method could be usefully applied into the stitching of 3D or 2D multiple images.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.75-82
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• 2009

The comparison of images uses PSNR generally. In the case that PSNR value is above 35, it is hard to distinguish the quality of images. In 2006 Lee has proposed the protocol to be able to prove ownership of image using publishing MSB bit strings of original image instead of original images and used the new function to measure correlation of MSB bit strings of two images. In the view of measuring the quality of images, correlation is a bit different from PSNR. That is, if an object image to gene ate from an original image has lower quality, PSNR has very low value, but though the quality is bad, correlation of the images is very high in the view of similarity. In this paper, we modify MSB comparison function that LEE suggested and propose the ICOR function, then analyze the possibility to decide correlation of two images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.347-365
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• 2013

The performance of finger-vein recognition methods is limited by camera optical defocusing, the light-scattering effect of skin, and individual variations in the skin depth, density, and thickness of vascular patterns. Consequently, all of these factors may affect the image quality, but few studies have conducted quality assessments of finger-vein images. Therefore, we developed a new finger-vein recognition method based on image quality assessment. This research is novel compared with previous methods in four respects. First, the vertical cross-sectional profiles are extracted to detect the approximate positions of vein regions in a given finger-vein image. Second, the accurate positions of the vein regions are detected by checking the depth of the vein's profile using various depth thresholds. Third, the quality of the finger-vein image is measured by using the number of detected vein points in relation to the depth thresholds, which allows individual variations of vein density to be considered for quality assessment. Fourth, by assessing the quality of input finger-vein images, inferior-quality images are not used for recognition, thereby enhancing the accuracy of finger-vein recognition. Experiments confirmed that the performance of finger-vein recognition systems that incorporated the proposed quality assessment method was superior to that of previous methods.

• Journal of Korea Multimedia Society
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• v.21 no.9
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• pp.1027-1034
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• 2018

CCTV has been known to possess high level of objectivity and utility. Hence, the government has recently focused on replacing low quality CCTV with higher quality ones or even by adding high resolution CCTV. However, converting all existing low-quality CCTV to high quality can be extremely costly. Furthermore, low quality videos prior to CCTV replacement are likely to be of poor quality and thus not utilized correctly. In order to solve these problems, this paper proposes a method to improve videos quality of images using SRGAN(Super Resolution Generative Advisory Networks). Through experiments, we have proven that it is possible to improve low quality CCTV videos clearly. For this experiment, a total of 4 types of CCTV videos were used and 10,000 images were sampled from each type. Those images could then be used for machine learning. The fact that the pre-process for machine learning has been done manually and the long time that required for machine learning seems to be complementary.

• ETRI Journal
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• v.38 no.6
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• pp.1114-1123
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• 2016

Multi-view video plus depth (MVD) has been widely used owing to its effectiveness in three-dimensional data representation. Using MVD, color videos with only a limited number of real viewpoints are compressed and transmitted along with captured or estimated depth videos. Because the synthesized views are generated from decoded real views, their original reference views do not exist at either the transmitter or receiver. Therefore, it is challenging to define an efficient metric to evaluate the quality of synthesized images. We propose a novel metric-the reduced-reference quality metric. First, the effects of depth distortion on the quality of synthesized images are analyzed. We then employ the high correlation between the local depth distortions and local color characteristics of the decoded depth and color images, respectively, to achieve an efficient depth quality metric for each real view. Finally, the objective quality metric of the synthesized views is obtained by combining all the depth quality metrics obtained from the decoded real views. The experimental results show that the proposed quality metric correlates very well with full reference image and video quality metrics.