• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.379-385
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• 2015

This paper proposes the hardware architecture of high performance ALF(Adaptive Loop Filter) for efficient filter coefficient estimation. In order to make the original image which has high resolution and high quality into highly compressed image effectively and also, subjective image quality into improved image, the ALF technique of HEVC performs a filtering by estimating filter coefficients using statistical characteristics of image. The proposed ALF hardware architecture is designed with a 2-step pipelined architecture for a reduction in performance cycle by analysing an operation relationship of Cholesky decomposition for the filter coefficient estimation. Also, in the operation process of the Cholesky decomposition, a square root operation is designed to reduce logic area, computation time and computation complexity by using the multiplexer, subtracter and comparator. The proposed hardware architecture is designed using Xilinx ISE 14.3 Vertex-7 XC7VCX485T FPGA device and can support 4K UHD@40fps in real time at a maximum operation frequency of 186MHz.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.163-176
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• 2022

As the business ecosystem has become more uncertain, the sources of supply chain risk have also been becoming more diverse. In particular, due to the development of informational technology in recent years, firms need to consider the emerging supply chain risk sources as well as traditional supply chain risk sources. A typical example is negative word-of-mouth by social media. Therefore, we investigated the virality of negative word-of-mouth on manufacturing firms by using YouTube as a representative social media. More specifically, we investigated how the social capital of the video creator influences the virality of negative word-of-mouth and how the emotional tone of the video affects the virality of negative word-of-mouth. In conclusion, the social capital of the video creator influenced the scale and speed of negative word-of-mouth. Furthermore, negative emotion words moderated the relation between the social capital of the video creator and the scale of negative word-of-mouth.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.12-21
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• 2006

In this paper, we propose a technique for extracting attentive objects in images using feature maps, regardless of the complexity of images and the position of objects. The proposed method uses feature maps with edge and color information in order to extract attentive objects. We also propose a reference map which is created by integrating feature maps. In order to create a reference map, feature maps which represent visually attentive regions in images are constructed. Three feature maps including edge map, CbCr map and H map are utilized. These maps contain the information about boundary regions by the difference of intensity or colors. Then the combination map which represents the meaningful boundary is created by integrating the reference map and feature maps. Since the combination map simply represents the boundary of objects we extract the candidate object regions including meaningful boundaries from the combination map. In order to extract candidate object regions, we use the convex hull algorithm. By applying a segmentation algorithm to the area of candidate regions to separate object regions and background regions, real object regions are extracted from the candidate object regions. Experiment results show that the proposed method extracts the attentive regions and attentive objects efficiently, with 84.3% Precision rate and 81.3% recall rate.

• Journal of radiological science and technology
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• v.38 no.4
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• pp.389-394
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• 2015

There is a progressive development in the medical imaging technology, especially of descriptive capability for anatomical structure of human body thanks to advancement of information technology and medical devices. But however maintenance of correct posture is essential for the medical imaging checkup on the shoulder joint requiring rotation of the upper limb due to the complexity of human body. In the cases of MRI examination, long duration and fixed posture are critical, as failure to comply with them leads to minimal possibility of reproducibility only with the efforts of the examiner and will of the patient. Thus, this study aimed to develop an auxiliary device that enables rotation of the upper limb as well as fixing it at quantitative angles for medical imaging examination capable of providing diagnostic values. An auxiliary device has been developed based on the results of precedent studies, by designing a 3D model with the CATIA software, an engineering application, and producing it with the 3D printer. The printer is Objet350 Connex from Stratasys, and acrylonitrile- butadiene-styrene(ABS) is used as the material of the device. Dimensions are $120{\times}150{\times}190mm$, with the inner diameter of the handle being 125.9 mm. The auxiliary device has 4 components including the body (outside), handle (inside), fixture terminal and the connection part. The body and handle have the gap of 2.1 mm for smooth rotation, while the 360 degree of scales have been etched on the handle so that the angle required for observation may be recorded per patient for traceability and dual examination.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.145-154
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• 2014

The road network becomes more complex and extensive. Therefore, the inconveniences are caused in accordance with the time delay of the restoration of damaged roads, demands for excessive costs on information collection, and limitations on acquisition of damage information of the roads. Recently, road centric spatial information is gathered using mobile multi sensor system for road inventory. But expensive MMS(Mobile Mapping System) equipments require high maintenance costs from beginning and takes a lot of time in the data processing. So research is needed for continuous maintenance by collecting and displaying the damaged information on a digital map using low cost mobile camera system. In this research we aim to develop the techniques for mosaic with a regular ground sample distance using successive image from oblique camera on a vehicle. For doing this, mosaic image is generated by estimating the homography of high resolution oblique image, and the ground sample distance and appropriate overlap are analyzed using high resolution aerial oblique images which contain resolution target. Based on this we have proposed the appropriate overlap and exposure interval for mobile road inventory system.

• 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.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.1
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• pp.22-31
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• 2007

The proposed algorithm in this paper is based on the wavelet decomposition and the energy computation of composed blocks so the amount of calculation and complexity is minimized by adaptively replacing the DWT coefficients and managing the resources effectively. We are now living in the world of a lot. of multimedia applications for many digital electric appliances and mobile devices. Among so many multimedia applications, the digital image compression is very important technology for digital cameras to store and transmit digital images to other sites and JPEG2000 is one of the cutting edge technology to compress still images efficiently. The digital cm technology is mainly using the digital image compression features so that those images could be efficiently saved locally and transferred to other sites without any losses. JPEG2000 standard is applicable for processing the digital images usefully to keep, send and receive through wired and/or wireless networks. The discrete wavelet transform (DWT) is one of the main differences to the previous digital image compression standard such as JPEG, performing the DWT to the entire image rather than splitting into many blocks. Several digital images m tested with this method and restored to compare to the results of conventional DWT which shows that the proposed algorithm get the better result without any significant degradation in terms of MSE & PSNR and the number of zero coefficients when the energy based adaptive DWT is applied.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.1
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• pp.27-37
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• 2002

The classification accuracy of land cover has been considered as one of the major issues to estimate pollution loads generated from diffuse landuse patterns in a watershed. This research aimed to assess the effects of the acquisition methods and sampling size of training reference data on the classification accuracy of land cover using an imagery acquired by optical sensor(OPS) on JERS-1. Two kinds of data acquisition methods were considered to prepare training data. The first was to assign a certain land cover type to a specific pixel based on the researchers subjective discriminating capacity about current land use and the second was attributed to an aerial photograph incorporated with digital maps with GIS. Three different sizes of samples, 0.3%, 0.5%, and 1.0% of all pixels, were applied to examine the consistency of the classified land cover with the training data of corresponding pixels. Maximum likelihood scheme was applied to classify the land use patterns of JERS-1 imagery. Classification run applying an aerial photograph achieved 18 % higher consistency with the training data than the run applying the researchers subjective discriminating capacity. Regarding the sample size, it was proposed that the size of training area should be selected at least over 1% of all of the pixels in the study area in order to obtain the accuracy with 95% for JERS-1 satellite imagery on a typical small-to-medium-size urbanized area.

• The Korean Journal of Nuclear Medicine Technology
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• v.12 no.3
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• pp.214-221
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• 2008

Purpose: We make a qualitative analysis of whether Fusion SPECT/CT can find lesion's anatomical sites better than existing SPECT or not, and we want to show the usefulness of SPECT/CT through finding out effects of CT attenuation correction on SPECT images. Materials and Method: 1. The evaluation of fusion images: This study comprised patients who was tested $^{131}I$-MIBG, Bone, $^{111}In$-Octreotide, Meckel's diverticulum, Parathyroid MIBI with Precedence 16 or Symbia T2 from 2008 Jan to Aug. We compared SPECT/CT image with non fusion image and make a qualitative analysis. 2. The evaluation of attenuation correction: We classified 38 patients who was tested 201Tl myocardial exam with Symbia T2 into 5 sections by using Cedars Sinai' QPS program - Ant, Inf, Lat, Septum, Apex. And we showed each section's perfusion states by percentage. We compared the each section's perfusion-states differences between CT AC and Non AC by average${\pm}$standard deviation. Results: 1. The evaluation of fusion images : In high energy $^{131}I$ cases, it was hard to grasp exact anatomical lesions due to difference between regions and surrounding lesions' uptake level. After combining with CT, we could grabs anatomical lesion more exactly. And in meckel's diverticulum case or to find lesions around bowels or organs with $^{111}In$ cases, it demonstrates its superiority. Bone SPECT/CT images help to distinguish between disk spaces certainly and give correct results. 2. The evaluation of attenuation correction: There is no significant difference statistically in Ant and Lat (p>0.05), but there is a meaningful difference in Inferior, Apex and Septum (p<0.05). AC perfusion at inferior wall in the 5 sections of myocardium: The perfusion difference between Non AC perfusion image ($68.58{\pm}7.55$) and CT corrected perfusion image ($76.84{\pm}6.52$) was the largest by $8.26{\pm}4.95$ (p<0.01, t=10.29). Conclusion: Nuclear medicine physicians can identify not only molecular image which shows functional activity of lesions but also anatomical location information of lesions with more accuracy using the combination of SPECT and CT systems. Of course this combination helps nuclear medicine physician find out the abnormal parts. Moreover combined data sets help separate between normal group and abnormal group in complicated body part. So clinicians can carry out diagnosis and treatment planning at the same time with a single test image. In addition, when we examine a myocardium in thorax where attenuation can occur easily, we can trust perfusion more in a certain region in SPECT test because CT provides the capability for accurate attenuation correction. In these reasons, we think we can prove the justice after treatment fusion image.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.