• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.9-12
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• 2000

This paper proposes an improved image illumination estimation method based on the conventional color constancy algorithm. The most important process of color constancy algorithm is the estimation of the spectral distributions of illuminant of an input image. To estimate of the spectral distributions of illuminant of an input image, we use the brightest pixel values and the values of surface reflectance of an input image using a principal component analysis of the given munsell chips. We estimate a CIE tristimulus values of an input image using the estimated .spectral distribution of illuminant and recover an image by scaling it regularity. From the experimental results, the proposed method was effective in estimating the image illumination

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.39-46
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• 2001

In this paper we propose a new method that can be estimation the spectral power distribution of the light source from three-band images. the light source is estimated by dividing the reflected spectral power distribution of the maximum achromatic region(L(λ)) by the corresponding surface reflectance(Ο(λ)). In order to obtain reflected spectral power distribution of the maximum achromatic region from three-bend images, a modified gray world assumption algorithm is adapted. And the maximum surface reflectance is estimated using the principal component analysis method along with achromatic population. The achromatic population is created from a set of given Munsell color chips whose chroma vector is less than threshold. Cumulative contribution ratio of principal components from the first to the third for classified achromatic population was about 99.75%. The reconstruction of illumination spectral power distribution by using achromatic population and three-band digital images captured under various light source was examined, and evaluated by RMSE between the original and reconstructed illumination spectral power distribution. This work was supported by grant No (2000-1-30200-005-3) from the Basic Research Program of the Korea Science & Engineering Foundation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.392-400
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• 2001

This paper proposes an illuminant estimation algorithm that estimates the spectral power distribution of an incident light source from a single image. The proposed illumination recovery procedure has two phases. First, the surface spectral reflectances are recovered in the maximum achromatic region (MAR) which is the most achromatic and highly bright region of an image after removing partially the effect of illumination using a modified gray world algorithm. Here, the surface reflectances of MAR are estimated using the principal component analysis method along with a set of given 1269 Munsell samples. Second, the Population of reflected lights is determined with 1269 Munsell samples and a set of illuminations then the spectral distribution of re(looted lights of MAR is selected from the spectral database. That is, color differences are compared between the reflected lights of the MAR and the spectral database, which is the set of reflected lights built by the given set of Munsell samples and illuminants. Then the closest colors from the spectral database are selected. Finally, the illuminant of an image can be calculated dividing the average spectral distributions of reflected lights of MAR by the average surface reflectances of the MAR. In order to evaluate the proposed algorithm, experiments with artificial scenes, which are exposed to chromatic illuminants, were performed and the spectral distribution of estimated illumination and color difference are compared with results of the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3A
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• pp.276-283
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• 2002

This paper proposes a new color constancy algorithm using the maximum luminance surface. This method uses a linear model which represents the characteristics of human visual system. The most important process of linear model is the estimation of the spectral distributions of illumination from an input image. To estimate of the spectral distributions of illumination from an input image, we first estimate spectral distribution functions of reflected light on the brightest surface. Then, we estimate surface reflectance functions corresponding to the maximum luminance surface using a principal component analysis of the given munsell chips. We finally estimate the spectral distributions of illumination in an image. Using an estimated illumination, we recover an image by scaling it regularly for the lightness calibration. From the experimental results, the proposed method was effective in recovering the color images compared with others.

• Journal of Korea Multimedia Society
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• v.4 no.2
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• pp.97-107
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• 2001

In this paper, an illuminant estimation algorithm of a chromatic digital images proposed. The proposed illumination estimation method has two phases. First, the surface spectral reflectances are recovered. In this case, the surface spectral reflectances recovered are limited to the maximum highlight region (MHR) which is the most achromatic and highly bright region of an image after applying intermediate color constancy process using a modified gray world algorithm. Next, the surface reflectances of the maximum highlight region are estimated using the principal component analysis method along with a set of given Munsell samples. Second, the spectral distribution of reflected lights of MHR is selected from the spectral database. That is a color difference is compared between the reflected lights of the MHR and the spectral database that is the set of reflected lights built by the given Munsell samples and a set of illuminants. Then the closest colors from the spectral database are selected. Finally, the illuminant of an image can be calculated dividing the average spectral distributions of reflected lights of MHR by the average surface reflectances of the MHR. In order to evaluate the proposed algorithm, experiments with artificial and real captured color-biased scenes were performed and numerical comparison examined. The proposed method was effective in estimating the spectral of the given illuminant sunder various illuminants.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.22 no.1
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• pp.11-18
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• 1986

Schooling behavier to a fishing gear and estimation of the volume of fish school in set net have ~ been studied by making use of such techniques as visual observations, underwater cameras, under- water televison. However, all of these observation techniques are subject to restrictions caused by illumination, underwater visibility, underwater transparent and sea conditions. For the above mentioned reasoa, one of the most effective method by this time become generally known a method using fish finder. In this paper, in order to control the fishing ground of set net effectively and to develope the telemetric fish finder, the experiments for the target strength, underwater shape of fishing gear, schooling behavier and volume of fish school with fish finder were performed at Galgott fishing ground of set net located Keouje Island, 15th-24th July and 18th-20th October in 1985. The results of these experiment showed that a method using fish finder in fishing grOlllld of set net is available for estimating distribution and school size, fish behavier in relation to a fishing gear and underwater shape of fishing gears.

• Proceedings of the Korean Printing Society Conference
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• 2000.04a
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• pp.35-44
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• 2000

Because Image on the CRT change under different illuminants, human is difficult to see original color of object. If what is information of used illuminant on capturing object know, image can be transformed according to viewing condition using the linear matrix method. To know information of used illuminant at an image, the spectral radiance of illuminant can be estimated using the linear model of Maloney and Wandell form an image. And then image can be properly transformed it using color appearance model. In this paper, we predict the spectral radiance of illuminant using spectral power distribution of specular light and using surface spectral reflectance at maximum gray area. and then we perform visual experiments for the corresponding color reproduction according to viewing condition. In results, we ensure that the spectral radiance of illuminant at an image can be well estimated using above algorithms and that human visual system is 70% adapted to the monitor's white point and 30% to ambient light when viewing softcopy images.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.3
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• pp.267-274
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• 2015

It is necessary to both analyze root-cause of non-conformance of effective illumination time to the specification, and estimate the storage lifetime for 81 mm illuminating projectile stockpiled over 10 years. In this paper, aging mechanism of magnesium flare material due to long-term storage was supposed, and two-stage tests, pre-test and main test based on accelerated degradation tests were performed. Field storage environment of moistureproof was set up, and illumination times in the accelerated degradation tests for temperatures 60 and $70^{\circ}C$ were measured. Then, storage reliability of the projectile was estimated through analyzing the measured data and applying distribution-based degradation models to the data. The $B_{10}$ life by which 10 % of a population of the projectiles will have failed at storage temperature of $25^{\circ}C$ was estimated about 7 years.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.24-35
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• 2016

By estimating environment light distribution, we can generate realistic shadow images in AR(augmented reality). When we estimate light distribution without sensing equipment, environment light model, geometry of virtual object, and surface reflection property are needed. Previous study using 3D marker builds surrounding light environment with a geodesic dome model and analyzes shadow images. Because this method employs candidate shadow maps in initial scene setup, however, it is difficult to estimate precise light information. This paper presents a novel light estimation method based on hierarchical light distribution model subdivision. By using an overlapping area ratio of the segmented shadow and candidate shadow map, we can make hierarchical subdivision of light geodesic dome.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1633-1641
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• 1996

In this paper we propose a new method for anlayzing the properties of surface reflectance and reconstructing the shape of object using estimated reflectance parameters. We have investigated the hybrid reflectance surface which has specularreflection and diffuse reflection, which can be explained by Torrance-Sparrow model. Sample sphere made on one maerial is used to estimate the reflectance properties by using LMS algorithm. We can make the reference image which consists of surface normal and brightness value using estimated reflectance parameters, and thenarbitrary shape object made of the same material as sample can be reconstructed by matching with reference image. Photometric matching method proposed in this paper is robust because it mateches object image with the reference imageconsidering its neighbor brightness distribution. Also, in this paper plate diffuse illumination is used to remove intensity disparity with simple scheme. It is expected that the proposed algorithm can be applied to 3D recognition, vision inspection system and other fields.