• Journal of the Optical Society of Korea
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• v.13 no.1
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• pp.139-145
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• 2009

Computational integral imaging (CII) is a new method for 3D imaging and visualization. However, it suffers from seriously poor image quality of the reconstructed image as the reconstructed image plane increases. In this paper, to overcome this problem, we propose a CII method based on a smart pixel mapping (SPM) technique for partially occluded 3D object recognition, in which the object to be recognized is located at far distance from the lenslet array. In the SPM-based CII, the use of SPM moves a far 3D object toward the near lenslet array and then improves the image quality of the reconstructed image. To show the usefulness of the proposed method, we carry out some experiments for occluded objects and present the experimental results.

• ETRI Journal
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• v.29 no.5
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• pp.649-654
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• 2007

In this paper, we propose a computational integral imaging reconstruction (CIIR) method using a round mapping model to improve the viewing quality of 3-D images. The proposed CIIR method can overcome the problem of non-uniformly reconstructed images caused by the conventional method. To show the usefulness of proposed method, some experiments are carried out and the results are presented.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1170-1178
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• 2021

This paper proposed a versatile algorithm based on a dual-tree complex wavelet transform for intensifying the visual aspect of medical images. First, the decomposition of the input image into a high sub-band and low-sub-band image is done. Further, to improve the resolution of the resulting image, the high sub-band image is interpolated using Lanczos interpolation. Also, contrast enhancement is performed by singular value decomposition (SVD). Finally, the image reconstruction is achieved by using an inverse wavelet transform. Then, the Gaussian filter will improve the visual quality of the image. We have collected images from the hospital and the internet for quantitative and qualitative analysis. These images act as a reference image for comparing the effectiveness of the proposed algorithm with the existing state-of-the-art. We have divided the proposed algorithm into several stages: preprocessing, contrast enhancement, resolution enhancement, and visual quality enhancement. Both analyses show the proposed algorithm's effectiveness compared to existing methods.

• Journal of Korea Multimedia Society
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• v.25 no.10
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• pp.1386-1394
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• 2022

As consumption of high-quality fruits increases and sales and packaging units become smaller, the demand for automatic fruit grading systems is increasing. Compared to other crops, the quality of fruit is determined by visual characteristics such as shape, color, and scratches, rather than just physical size and weight. Accordingly, this study presents a CNN model that can effectively extract and classify the visual features of fruits and a perceptron that classifies fruits using physical features, and proposes a stacking ensemble model that can effectively combine the classification results of these two neural networks. The experiments with AI Hub public data show that the stacking ensemble model is effective for grading fruits. However, the ensemble model does not always improve the performance of classifying all the fruit grading. So, it is necessary to adapt the model according to the kind of fruit.

• Journal of Environmental Science International
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• v.23 no.2
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• pp.239-248
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• 2014

This study investigated the effects of soil depths and soil organic fertilizer application on the growth characteristics of Spiraea bumalda 'Gold Mound' in a extensive green roof system. The treatments were 3 soil depths (10, 15 and 25 cm) and 5 soil types in mixture of artificial soil and organic fertilizer. We measured plant height, leaf width, leaf length, number of flowers, visual quality and survival rate from March to October in 2011. The growing medium of 10 cm soil depth showed the highest plant growth in $A_1$ (amended soil 100%), and the lowest plant growth in $O_1A_4$ (organic fertilizer 20% + amended soil 80%) treatment. In case of 15 cm soil depth, Spiraea bumalda 'Gold Mound' showed a high leaf length and visual quality in $O_1A_2$(organic fertilizer 33% + amended soil 67%) treatment and high leaf width and number of flowers in $O_1$ (organic fertilizer 100%) treatment. $A_1$ treatment without organic fertilizer showed the lowest leaf length and poorest visual quality, and $O_1A_4$ treatment showed the lowest plant height and lowest number of flowers. At soil depth 25 cm, $O_1A_1$ (organic fertilizer 50% + amended soil 50%) treatment showed greater plant height, visual quality and number of flowers than other treatments. The leaf length and leaf width were more effective in $O_1$ treatment. $A_1$ treatment showed a relatively low leaf length, leaf width and visual quality. The higher the organic conditioner, the better the plant growth. And, survival rates of Spiraea bumalda 'Gold Mound' showed 92%, 88% and 76% at soil depths of 25 cm, 15 cm and 10 cm, respectively, in this a extensive green roof system. Therefore, the results showed that the growth of Spiraea bumalda 'Gold Mound' was affected by both soil quality and soil depth. Different optimal mixtures of organic fertilizer and amended soil were determined, depending upon soil depth.

• Asian Journal of Turfgrass Science
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• v.26 no.2
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• pp.116-122
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• 2012

The study was conducted to know whether turfgrass wear tolerance, growth, and quality could be improved by the application of silicon and potassium. First, turf responses to silicate and potassium were evaluated by several parameters such as, turf visual quality, root length, shoot density, and dry weight under the field condition. Second, turf responses to traffic frequencies were examined by turf growth (root) length, shoot density and dry weight) and soil hardness under the field condition. Finally, under traffic stress condition, the effects of silica and potassium application on wear tolerance were evaluated through the methods described above. Creeping bentgrass (Agrostis stolonifera) rooting were significantly improved by silica. The root length was enhanced by an increase in potassium silicate application. Certain level of light traffic is beneficial while frequent traffic cause serious adverse effect on visual quality of bentgrass. Under a traffic stress condition with 10 times of footing a day for 30 days, silica and potassium increased turf visual quality by 6.38% and 10.25% respectively when compared to the control. Silica and potassium treatment on trafficked plot increased turf visual quality by 11.4% and 10.2% respectively in comparison with the control with significant reduction of wear injury from the traffic. A co-application of potassium silicate with potassium sulfate provided the enhanced visual quality of turf as compared to application of silica or potassium fertilizer, respectively.

• Journal of Korean Society of Forest Science
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• v.85 no.2
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• pp.195-209
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• 1996

The purpose of this study is to suggest objective basic data for the national park development through the quantitative analysis of the visual quality included in the physical environment of the Dukyu National Park. For this, spatial images structure of physical elements have been analyzed by factor analysis algorithm and degree of visual quality have been measured mainly by questionnaires. Result of this thesis can be summarized as follows. Factors covering the spatial image of the Dukyu National Park landscape have been found to be the overall synthetic evaluation spatial, appeal, natural quality and physical factors such as the overall the synthetic evaluation, spatial and appear yield high factor scores. Thus, these factors can be considered to represent the site spatial image of Dukyu Korean-National Park. By using the control method for the number of factors, Total variance explained by the factors has been obtained as 45.46% and 45.45%. Principal variables of main factors explained above may be the scaling containing the functional criteria of quantitative approach for landscape management of national park development. According to difference of special image from each place, for these variables that decided the visual quality can be differed, and even the same place due to landscape control point change the visual quality can be affected affirmately or negatively, according to recognized by the landscape control point.

• Journal of Korean Ophthalmic Optics Society
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• v.12 no.3
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• pp.111-115
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• 2007

Purpose: The aim of this study was to assess vision-related quality of life and modes of refractive error correction. We administered NEI-VFQ (National Eye Institute Visual Function Questionnaire) to 137 subjects in two modes of refractive error correction: spectacles and contact lens wearers. The NEL-VFQ was developed to assess vision-related quality of life with respect to 1) visual symptoms 2) social function as well as difficulty with tasks and symptoms 3) economic issues and health concerns 4) psychological well-being. The NEL-VFQ was translated from English into Korean. Methods: All data were analyzed using SAS 8.0. Student's T-test was conducted to determine significant differences in each of the subscale (${\alpha}=0.05$). Result: The Peripheral Vision subscale score ($mean{\pm}SD$) was $52.2{\pm}32.7$ for the spectacle wearers, $88.6{\pm}18.1$ for contact lens wearers; the spectacle wearers' Peripheral Vision score was significantly lower than contact lens wearers (p=0.0001). There were also significant differences between two groups detected in Color Vision (p=0.001), General Vision (p=0.01) and Health Perception (p=0.01). Conclusion: Contact lens wearers and spectacle wearers were mostly high vision-related quality of life except General Vision and Health Perception. Especially, contact lens wearers were higher vision-related quality of life than spectacle wearers. Further studies on developing of good quality of contact lens will be needed to improve quality of life in ametropia.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.157-168
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• 2016

In image processing and computer vision fields, mean squared error (MSE) has popularly been used as an objective metric in image quality optimization problems due to its desirable mathematical properties such as metricability, differentiability and convexity. However, as known that MSE is not highly correlated with perceived visual quality, much effort has been made to develop new image quality assessment (IQA) metrics having both the desirable mathematical properties aforementioned and high prediction performances for subjective visual quality scores. Although recent IQA metrics having the desirable mathematical properties have shown to give some promising results in prediction performance for visual quality scores, they also have high computation complexities. In order to alleviate this problem, we propose a new fast IQA metric using a simple Laplace operator. Since the Laplace operator used in our IQA metric can not only effectively mimic operations of receptive fields in retina for luminance stimulus but also be simply computed, our IQA metric can yield both very fast processing speed and high prediction performance. In order to verify the effectiveness of the proposed IQA metric, our method is compared to some state-of-the-art IQA metrics. The experimental results showed that the proposed IQA metric has the fastest running speed compared the IQA methods except MSE under comparison. Moreover, our IQA metric achieves the best prediction performance for subjective image quality scores among the state-of-the-art IQA metrics under test.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1354-1363
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• 1993

Optical methods were developed to examine their feasibility for quality evaluation of peanut with pod. Surface color and internal quality of peanut were measured without contact. The surface color of peanut was measured by light reflectance at a region of visible wavelengths. Its characteristic was high correlated with a visual grading of peanut. A trial machine for the color grading of peanut was developed using an optical sensor and it was considered to compare with the visual grading. The spectral reflectance at a region of near infrared wavelengths from 1,200 to 2,500nm was measured , and the chemical components of peanut were related to spectral reflectance at special wavelengths. The protein, fat and moisture contents of peanut were estimated by the near infrared methods. An infrared imaging method was developed to evaluate the internal quality of peanut with pod. As thermal characteristic of peanut with pod was deeply related to internal quality , the quality of peanut can be evaluated by temperature changes on the surface of peanut. Measurement of surface color, near infrared reflectance and thermal imaging were shown to be very effective in grading of peanut with pod.