• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.121-133
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• 2005

Texture imaging, which means texture image creation by co-occurrence relation, has been known as one of the useful image analysis methodologies. For this purpose, most commercial remote sensing software provides texture analysis function named GLCM (Grey Level Co-occurrence Matrix). In this study, texture-imaging program based on GLCM algorithm is newly implemented. As well, texture imaging modules for GLDV (Grey Level Difference Vector) are contained in this program. As for GLCM/GLDV Texture imaging parameters, it composed of six types of second order texture functions such as Homogeneity, Dissimilarity, Energy, Entropy, Angular Second Moment, and Contrast. As for co-occurrence directionality in GLCM/GLDV, two direction modes such as Omni-mode and Circular mode newly implemented in this program are provided with basic eight-direction mode. Omni-mode is to compute all direction to avoid directionality complexity in the practical level, and circular direction is to compute texture parameters by circular direction surrounding a target pixel in a kernel. At the second phase of this study, some case studies with artificial image and actual satellite imagery are carried out to analyze texture images in different parameters and modes by correlation matrix analysis. It is concluded that selection of texture parameters and modes is the critical issues in an application based on texture image fusion.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.768-779
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• 2018

In this paper, we propose a novel video quality function for video processing based on MSSSIM to select an appropriate video processing filter and to accommodate multiple processing filters to each pixel block in a picture frame by a mathematical selection law so as to maintain video quality and to reduce the bitrate of compressed video. In viewpoint of video compression, since the properties of video quality and bitrate is different for each picture of video frames and for each areas in the same frame, it is difficult for the video filter with single property to satisfy the object of increasing video quality and decreasing bitrate. Consequently, to maintain the subjective video quality in spite of decreasing bitrate, we propose the methodology about the MSSSIM as the measure of subjective video quality, the KL-Divergence as the measure of bitrate, and the combination method of those two measurements. Moreover, using the proposed combinatorial measurement, when we use the multiple image filters with mutually different properties as a pre-processing filter for video, we can verify that it is possible to compress video with maintaining the video quality under decreasing the bitrate, as possible.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.105-112
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• 2023

In this paper, we propose a new method for displaying colored defects by measuring the relative density with the wide-area and local densities of X-ray. The relative density of one pixel represents a relative difference from the surrounding pixels, and we also suggest a colorization of X-ray images representing these pixels as normal and defective. The traditional method mainly inspects materials such as plastics and metals, which have large differences in transmittance to the object. Our proposed method can be used to detect defects such as sprouts or holes in images obtained by an inspection machine that detects X-rays. In the experiment, the products that could not be seen with the naked eye were colored with pests or sprouts in a specific color so that they could be used in the agricultural product selection system. Products that are uniformly filled with a single ingredient inside, such as potatoes, carrots, and apples, can be detected effectively. However, it does not work well with bumpy products, such as peppers and paprika. The advantage of this method is that, unlike machine learning, it doesn't require large amounts of data. The proposed method could be applied to a screening system using X-rays and used not only in agricultural product screening systems but also in manufacturing processes such as processed food and parts manufacturing, so that it can be actively used to select defective products.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.1
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• pp.94-100
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• 2011

Purpose: Basal/Acetazolamide-challenged brain perfusion SPECT is very useful to assess cerebral perfusion and vascular reserve. However, as there is a trade off between sensitivity and spatial resolution in the selection of collimator, the selection of optimal collimator is crucial. In this study, we examined three collimators to select optimal one for 1-day brain perfusion SPECT. Materials and Methods: Three collimators, low energy high resolution-parallel beam (LEHR-par), ultra resolution-fan beam (LEUR-fan) and super fine-fan beam (LESFR-fan), were tested for 1-day imaging using Triad XLT 9 (TRIONIX). The SPECT images of Hoffman 3D brain phantom filled with 99mTc of 170 MBq and a normal volunteer were acquired with a protocol of 50 kcts/frame and detector rotation of 3 degree. Filterd backprojection (FBP) reconstruction with Butterworth filter (cut off frequencies, 0.3 to 0.5) was performed. The quantitative and qualitative assessments for three collimators were performed. Results: The blind tests showed that LESFR-fan provided the best image quality for Hoffman brain phantom and the volunteer. However, images for all the collimator were evaluated as 'acceptable'. On the other hand, in order to meet the equivalent signal-to-noise ratio (SNR), total acquisition time or radioactivity dose for LESFR-fan must have been increased up to almost twice of that for LEUR-fan and LEHR-par. The volunteer test indicated that total acquisition time could be reduced approximately by 10 to 14 min in clinical practice using LEUR-fan and LEHR-par without significant loss on image quality, in comparison with LESFR-fan. Conclusion: Although LESFR-fan provides the best image quality, it requires significantly more acquisition time than LEUR-fan and LEHR-par to provide reasonable SNR. Since there is no significant clinical difference between three collimators, LEUR-fan and LEHR-par can be recommended as optimal collimators for 1-day brain perfusion imaging with respect to image quality and SNR.