• Ocean and Polar Research
• /
• v.33 no.1
• /
• pp.1-11
• /
• 2011

This study describes measurements of fast ice recorded on May 23, 2009, in Kongsfjorden (translated as 'Kongs Fjord'), an inlet on the west coast of Spitsbergen in the Svalbard Archipelago. Seasonal fast ice is an important feature for Svalbard fjords, both in relation to their physical environment and also the local ecosystem, since it grows seaward from the coast and remains in place throughout the winter. Ice thickness, snow, ice properties, and wind speed were measured, while SAR (Synthetic Aperture Radar) data was observed simultaneously observed two times from ALOS-PALSAR (L-band). Measured ice thickness was about 25-35 cm while the thickness of ice floe broken from fast ice was measured as 10-15 cm. Average salinity was 1.9-2.0 ppt during the melting period. Polarimetric data was used to extract H/A/alpha-angle parameters of fast ice, ice floe, snow and glacier, which was classified into 18 classes based on these parameters. It was established that the area of fast ice represents surface scattering which indicates low and medium entropy surface scatters such as Bragg and random surfaces, while fast ice covered with snow belongs to a zone of low entropy surface scattering similar to snow-covered land surfaces. The results of this study will contribute to various interpretations of interrelationships between H/A/alpha parameters and the wave scattering Phenomenon of sea ice.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2006.11a
• /
• pp.237-238
• /
• 2006

The electrical properties such as dielectric constants and dielectric losses in the spinel samples of $LiGaTiO_4$, Li(Ga,Eu)$TiO_4$, $Li(Ga.Yb)TiO_4$ have been characterized by varying measuring temperature and frequency. The long range order structures are analyzed by rietveld refinement method. and local atomic disorder structures are analyzed by MEM (maximum entropy method). The relation between the crystal structure and dielectric properties are discussed. $LiGaTiO_4$ spinel has the IMMA with lattice constant, a = 5.86333, b=17.5872. c = 8.28375 ${\AA}$, Li-sites are partially substituted by Ga or Ti. Two crystallographic oxygen sites are partially occupied(40~50%). The dielectric constants of $LiGaTiO_4$, $LiYbTiO_4$, and $LiGa_{2/6}Eu_{1/6}Ti_{1.5}O_4$ ceramics were 127, 75 and 272, respectively at 100 kHz. The dielectric relaxation were observed in the $LiGaTiO_3$ ceramics and the temperature where dielectric loss shows maximum was $390^{\circ}C$ at 1 kHz and increased with increasing the measuring frequency.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.10
• /
• pp.97-107
• /
• 2015

The initial X-ray images obtained from a digital X-ray machine have a wide data range and uneven brightness level than normal images. In particular, in Chest X-ray images, it is necessary to improve naturally all of the parts such as ribs, spine, tissue, etc. These X-ray images can not be improved enough from conventional image quality enhancement algorithms because their characteristics are different from ordinary images'. This paper proposes to eliminate unnecessary background from an input image and expand the histogram range of the image. Then, we adjust the weight per frequency band of the image for improvement of contrast and sharpness. Finally, jointly taking the advantages of global contrast enhancement and local contrast enhancement methods we obtain an improved X-ray image suitable for effective diagnosis in comparison with the existing methods. Experimental results show quantitatively that the proposed algorithm provides better X-ray images in terms of the discrete entropy and saturation than the previous works.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.7
• /
• pp.2769-2784
• /
• 2020

This paper aims to compare the scenic images of four ancient Chinese cities including Lijiang, Pingyao, Huizhou and Langzhong, so as to provide specific development strategies for the ancient cities. In this paper, the ancient cities' scenic images are divided into three sub-indexes and eight evaluation dimensions. Based on this, the study first uses Python software to collect tourists' online comments on the four ancient cities. Then, the social network analysis method is used to build a high-frequency keywords matrix of tourist comments and the R language is used to generate a visual network graph. After this, the entropy weight method is used to determine the weights and values of eight evaluation dimensions. Finally, the tourists' overall satisfaction indexes of the four ancient cities are calculated accordingly. The results show that (1) the overall satisfaction of Lijiang is the highest, while that of Huizhou is the lowest; (2) from the weight of each evaluation dimension, it can be seen that tourists care more about the national culture and historical culture; (3) from tourists' satisfaction index on each evaluation dimension of the four ancient cities, we can find that the four ancient cities has their own advantages and disadvantages in tourism development. (4) local tourism-related institutions should strengthen their advantages and improve their deficiencies so as to enhance tourists' overall image of the ancient city.

• Korean Journal of Remote Sensing
• /
• v.26 no.5
• /
• pp.581-591
• /
• 2010

In this paper, we proposed a new wavelet-based image fusion algorithm, which has advantages in both frequency and spatial domains for signal analysis. The developed algorithm compares the ratio of SAR image signal to optical image signal and assigns the SAR image signal to the fused image if the ratio is larger than a predefined threshold value. If the ratio is smaller than the threshold value, the fused image signal is determined by a weighted sum of optical and SAR image signal. The fusion rules consider the ratio of SAR image signal to optical image signal, image gradient and local variance of each image signal. We evaluated the proposed algorithm using Ikonos and TerraSAR-X satellite images. The proposed method showed better performance than the conventional methods which take only relatively strong SAR image signals in the fused image, in terms of entropy, image clarity, spatial frequency and speckle index.

• Journal of KIISE:Software and Applications
• /
• v.31 no.12
• /
• pp.1684-1690
• /
• 2004

This paper presents a method for classifier selection that uses distribution information of the training samples in a small region surrounding a sample. The conventional DCS-LA(Dynamic Classifier Selection - Local Accuracy) selects a classifier dynamically by comparing the local accuracy of each classifier at the test time, which inevitably requires long classification time. On the other hand, in the proposed approach, the best classifier in a local region is stored in the FSA(Feature Space Attribute) table during the training time, and the test is done by just referring to the table. Therefore, this approach enables fast classification because classification is not needed during test. Two feature space attributes are used entropy and density of k training samples around each sample. Each sample in the feature space is mapped into a point in the attribute space made by two attributes. The attribute space is divided into regular rectangular cells in which the local accuracy of each classifier is appended. The cells with associated local accuracy comprise the FSA table. During test, when a test sample is applied, the cell to which the test sample belongs is determined first by calculating the two attributes, and then, the most accurate classifier is chosen from the FSA table. To show the effectiveness of the proposed algorithm, it is compared with the conventional DCS -LA using the Elena database. The experiments show that the accuracy of the proposed algorithm is almost same as DCS-LA, but the classification time is about four times faster than that.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.4
• /
• pp.164-174
• /
• 2015

In a real scenario, radiometric change has frequently occurred in the stereo image acquisition process using multiple cameras with geometric characteristics or moving a single camera because it has different camera parameters and illumination change. Conventional stereo matching algorithms have a difficulty in finding correct corresponding points because it is assumed that corresponding pixels have similar color values. In this paper, we present a new method based on the local descriptor reflecting intensity, gradient and texture information. Furthermore, an adaptive weight for local descriptor based on the entropy is applied to estimate correct corresponding points under radiometric variation. The proposed method is tested on Middlebury datasets with radiometric changes, and compared with state-of-the-art algorithms. Experimental result shows that the proposed scheme outperforms other comparison algorithms around 5% less matching error on average.

• Journal of the Society of Disaster Information
• /
• v.17 no.2
• /
• pp.206-217
• /
• 2021

Purpose: Recently, a series of large social disasters have led to a lot of research to prevent social disasters as well as natural disasters and reduce damage. However, this paper aims to select the types of social disasters that local governments should focus on and create basic data for effective countermeasures and mitigation efforts. Method: Among 43 types of disasters announced by the Ministry of Public Administration and Security, 11 types of disasters were selected and collected to select the main types of disasters, and risk types were derived by region with risk maps. In order to derive the risk map, each detailed index was rescheduled to be 0-1 and weights were determined through entropy technique. Result: As a result, about 41% of the major disasters announced by the Ministry of Public Administration and Security were consistent, and the rest of the major types were disasters that could not be obtained or have not occurred in the past 20 years. Conclusion: Therefore, in order to establish an effective prevention and recovery plan for social disasters through this study, it was intended to present social disaster-focused disasters for each local government.

• Journal of Broadcast Engineering
• /
• v.22 no.5
• /
• pp.608-617
• /
• 2017

Methods of contrast enhancement have problem such as side effect of over-enhancement with non-gaussian histogram distribution, tradeoff enhancement efficiency against brightness preserving. In order to enhance contrast at various histogram distribution, segmentation to region with gaussian distribution and then enhance contrast each region. First, we segment an image into several regions using GMM(Gaussian Mixture Model)fitting by that k-mean clustering and EM(Expectation-Maximization) in $L^*a^*b^*$ color space. As a result region segmentation, we get the region map and probability map. Then we apply local contrast enhancement algorithm that mean shift to minimum overlapping of each region and preserve brightness histogram equalization. Experiment result show that proposed region based contrast enhancement method compare to the conventional method as AMBE(AbsoluteMean Brightness Error) and AE(Average Entropy), brightness is maintained and represented detail information.

• Journal of Information Processing Systems
• /
• v.10 no.1
• /
• pp.145-161
• /
• 2014

Recently, many large organizations have multiple data sources (MDS') distributed over different branches of an interstate company. Local patterns analysis has become an effective strategy for MDS mining in national and international organizations. It consists of mining different datasets in order to obtain frequent patterns, which are forwarded to a centralized place for global pattern analysis. Various synthesizing models [2,3,4,5,6,7,8,26] have been proposed to build global patterns from the forwarded patterns. It is desired that the synthesized rules from such forwarded patterns must closely match with the mono-mining results (i.e., the results that would be obtained if all of the databases are put together and mining has been done). When the pattern is present in the site, but fails to satisfy the minimum support threshold value, it is not allowed to take part in the pattern synthesizing process. Therefore, this process can lose some interesting patterns, which can help the decider to make the right decision. In such situations we propose the application of a probabilistic model in the synthesizing process. An adequate choice for a probabilistic model can improve the quality of patterns that have been discovered. In this paper, we perform a comprehensive study on various probabilistic models that can be applied in the synthesizing process and we choose and improve one of them that works to ameliorate the synthesizing results. Finally, some experiments are presented in public database in order to improve the efficiency of our proposed synthesizing method.