• Journal of Information Processing Systems
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• v.17 no.5
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• pp.1004-1019
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• 2021

To solve the problems of the low image contrast, fuzzy edge details and edge details missing in noisy image fusion, this study proposes a noisy infrared and visible light image fusion algorithm based on non-subsample contourlet transform (NSCT) and an improved bilateral filter, which uses NSCT to decompose an image into a low-frequency component and high-frequency component. High-frequency noise and edge information are mainly distributed in the high-frequency component, and the improved bilateral filtering method is used to process the high-frequency component of two images, filtering the noise of the images and calculating the image detail of the infrared image's high-frequency component. It can extract the edge details of the infrared image and visible image as much as possible by superimposing the high-frequency component of infrared image and visible image. At the same time, edge information is enhanced and the visual effect is clearer. For the fusion rule of low-frequency coefficient, the local area standard variance coefficient method is adopted. At last, we decompose the high- and low-frequency coefficient to obtain the fusion image according to the inverse transformation of NSCT. The fusion results show that the edge, contour, texture and other details are maintained and enhanced while the noise is filtered, and the fusion image with a clear edge is obtained. The algorithm could better filter noise and obtain clear fused images in noisy infrared and visible light image fusion.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.1
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• pp.46-51
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• 2007

In this paper, we propose a new data clustering method using local probability and hypothesis theory. To cluster the test data set we analyze the local area of the test data set using local probability distribution and decide the candidate class of the data set using mean standard deviation and variance etc. To decide each class of the test data, statistical hypothesis theory is applied to the decided candidate class of the test data set. For evaluating, the proposed classification method is compared to the conventional fuzzy c-mean method, k-means algorithm and Discriminator analysis algorithm. The simulation results show more accuracy than results of fuzzy c-mean method, k-means algorithm and Discriminator analysis algorithm.

• Proceedings of the KSRS Conference
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• v.1
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• pp.316-319
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• 2006

Monthly-mean aerosol parameters derived from the 1998-2004 SeaWiFS observations over East Asian waters are analyzed. SeaWiFS GAC Level 1 data covering the Northeast Asian area are collected and processed by the standard atmospheric correction algorithm released by the SeaWiFS Project to produce daily aerosol optical thickness (AOT) and ${{\AA}}ngstr{\ddot{o}}m$ exponent imageries. Monthly mean AOT and ${{\AA}}ngstr{\ddot{o}}m$ exponent values are extracted from the daily composite images for six study areas chosen from the surrounding waters of Japan. A slight increasing trend of ${{\AA}}ngstr{\ddot{o}}m$ exponent is found and interpreted as about 4-5% increase in submicron fraction of aerosol optical thickness at 550nm. Two cloud screening methods, including the standard cloud masking method of SeaWiFS and the one based on the local variance method, are applied to the SeaWiFS data processing, in an attempt to inspect the influence to the observed statistical uptrend which probably induced by different cloud mask algorithms. The variability comes from the different cloud masking algorithms are discussed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.93-101
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• 2017

The distribution of inter-annual variation in temperature would help evaluate the likelihood of a climatic risk and assess suitable zones of crops under climate change. In this study, we evaluated two methods to estimate the standard deviation of temperature in the areas where weather information is limited. We calculated the monthly standard deviation of temperature by collecting temperature at 0600 and 1500 local standard time from 10 automated weather stations (AWS). These weather stations were installed in the range of 8 to 1,073m above sea level within a mountainous catchment for 2011-2015. The observed values were compared with estimates, which were calculated using a geospatial correction scheme to derive the site-specific temperature. Those estimates explained 88 and 86% of the temperature variations at 0600 and 1500 LST, respectively. However, it often underestimated the temperatures. In the spring and fall, it tended to had different variance (e.g., increasing or decreasing pattern) from lower to higher elevation with the observed values. A regression analysis was also conducted to quantify the relationship between the standard deviation in temperature and the topography. The regression equation explained a relatively large variation of the monthly standard deviation when lapse-rate corrected temperature, basic topographical variables (e.g., slope, and aspect) and topographical variables related to temperature (e.g., thermal belt, cold air drainage, and brightness index) were used. The coefficient of determination for the regression analysis ranged between 0.46 and 0.98. It was expected that the regression model could account for 70% of the spatial variation of the standard deviation when the monthly standard deviation was predicted by using the minimum-maximum effective range of topographical variables for the area.

• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.1
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• pp.41-51
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• 1999

This study was conducted to investigate the effects of local climatic conditions on the annual increment of Korean white pine planted in Gapyung and Yaungdong. For this, stand variables such as mean DBH, mean height, basal area per hectare, and volume per hectare by stand age were measured and summarized for each locality. Based on these statistics, annual increments for 8 years from stand age 10 to 18 were calculated for each of stand variables. A topoclimatological technique which makes use of empirical relationships between the topography and the weather in study sites was applied to produce normal estimates of monthly mean, maximum, minimum temperatures, relative humidity, precipitation, and hours of sunshine. Then, the yearly climatic variables from 1990 to 1997 for each study site were derived from the spatial interpolation procedures based on inverse- distance weighting of the observed deviation from the climatic normals at the nearest 11 standard weather stations. From these estimates, 17 weather variables such as warmth index, coldness index, index of aridity etc., which affect the tree growth, were computed on yearly base for each locality. The deviations of measured annual increments from the expected annual increments for 8 years based on yield table of Korean white pine were then correlated with and regressed on the yearly weather variables to examine effects of local climatic conditions on the growth. Gapyung area provides better conditions for the growth of Korean white pine in the early stage than Youngdong area. This indicates that the conditions such as low temperature, high relative humidity, and large amount of precipitation provide favor environment for the early growth of Korean white pine. A ccording to the correlation and regression an analysis using local climatic conditions and annual increments, the growth pattern of Gapyung area corresponds to this tendency. However, it was found that the relationship between annual increments and local climatic conditions in Youngdong area shows different tendency from Gapyung. These results mean that the yearly growth pattern could not sufficiently be explained by climatic conditions with high variance in yearly weather variables. In addition, the poor growth in Youngdong area might not only be affected by climatic conditions, but also by other environmental factors such as site quality.

• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.81-93
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• 2013

The selection of land for fishing village development project, and the standard used to classify fishing villages has been determined based on the guidelines developed by fishing village cooperatives. The approach fishing village cooperatives follows is likely to classify fishing villages without first reflecting on the overall development environment of the region, such as other industries and workers in the area. It also acts as a barrier for business promotion or evaluation, because the cooperatives do not match the administrative districts, which are the units of administration, and the main policy enforcement agent in regional development. Against this background, this study aimed to identify categories to situate the development direction, as well as the size and distribution of fishing villages based on eup, myeon, and dong administrative units as defined by the Fishing Villages and Fishery Harbors Act. This study was based on the Census of Agriculture, Forestry, and Fisheries of 2010, and analyzed 826 eups, myeon, and dongs with fishery households using the principal component analysis, and 2-Step cluster analysis methods. Therefore, 95% of the variance was explained using the covariance matrix for types of fishing villages, but it was analyzed as one component focusing on the number and ratio of fishery households, and used the cluster-type analysis, which focused on the sizes of fishing villages. The clusters were categorized into three types: (1) the development type based on the number of fishermen in the eups, myeons and dongs was analyzed as village size (682); (2) administrative district size (121); and (3) total eups, myeons and dongs (23), which revealed that the size of most fishing villages was small. We could explain 73% of the variance using the correlation coefficient matrix, which was divided into three types according to the three principal component scores, namely fishery household power, fishery industry power, and fishing village tourism power. Most fishing villages did not have a clear development direction because all business areas within the region were diversified, and 552 regions could be categorized under the harmonious development type, which is in need of balanced development. The fishery industry type typified by industrial strength included 159 regions in need of an approach based on industrialization of fishery product processing. Specialized production areas, which specialized in producing fishery products, were 115 regions with a high percentage of fishermen. The analysis results indicated that various situations in terms of size and development of fishing villages existed. However, because several regions exist in the form of small village units, it was necessary to approach the project in a manner that directed the diversification of regional development projects, such as places for local residents to relax or enjoy tourism experiences within the region, while considering the overall conditions of the relevant eups, myeons, and dongs. Reinforcement of individual support for fishermen based on the Fisheries Act must take precedence over providing support for fishermen through regional development. In addition, it is necessary to approach the development of fishing villages by focusing on industrializing the processing techniques of fishery products. Areas specialized in the production of fishery products are required to consider the facilities for fisheries production, and must make efforts to increase fishery resources, such as releasing fry.