• Journal of the Korean Graphic Arts Communication Society
• /
• v.16 no.3
• /
• pp.121-131
• /
• 1998

The object color does not look same under the different light source. It depends on the surface spectral reflectance and the spectral distribution of light source. Therefore we should find the surface spectral reflectance of object color and the spectral distribution of light source for color reproduction. Using Wiener estimation, we can estimate the spectral reflectance from low dimensional images obtained with multi-band image acquisition system. The kind and the number of imaging filters have the effect on the estimation of the spectral reflectance. Therefore it is important that optimal filters are selected to minimize the error of the result. In this paper, we describe methods to select optimal filters with minimum error between measured and estimated surface spectral reflectance and to estimate surface spectral reflectance of Munsell color chart from six multi-band images by using Wiener estimation.

• Proceedings of the Korean Printing Society Conference
• /
• 1998.10a
• /
• pp.1-6
• /
• 1998

The object color does not look same under the different light source. It depends on the surface spectral reflectance and the spectral distribution of light source. Therefore we should find the surface spectral reflectance of object color and the spectral distribution of light source for color reproduction. Using Winer estimation, we can reconstruct the spectral reflectance from low dimensional images obtained with a few filters. The kind and the number of filters have the effect on the estimation of the spectral reflectance. Therefore it is important that optimal filters are selected to minimize the error of the result. In this paper, we describe methods to select optimal filters with minimum error between measured and estimated surface spectral reflectance and to estimate surface spectral reflectance of Munsell color from six band images by using Wiener estimation.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2001.05a
• /
• pp.280-287
• /
• 2001

The studies to estimate the surface spectral reflectance of an object have received widespread attention using the multi-spectral camera system. However, the multi-spectral camera system requires the additional color filter according to increment of the channel and system complexity is increased by multiple capture. Thus, this paper proposes an algorithm to reduce the estimation error of surface spectral reflectance with the conventional 3-band RGB camera. In the proposed method, adaptive principal components for each pixel are calculated by renewing the population of surface reflectances and the adaptive principal components can reduce estimation error of surface spectral reflectance of current pixel. To evacuate performance of the proposed estimation method, 3-band principal component analysis, 5-band wiener estimation method, and the proposed method are compared in the estimation experiment with the Macbeth ColorChecker. As a result, the proposed method showed a lower mean square ems between the estimated and the measured spectra compared to the conventional 3-band principal component analysis method and represented a similar or advanced estimation performance compared to the 5-band wiener method.

• Journal of Korea Multimedia Society
• /
• v.18 no.12
• /
• pp.1439-1444
• /
• 2015

Measuring spectral reflectance can be regarded as obtaining inherent color parameters, and spectral reflectance has been used in image processing. Model-based spectrum recovering, one of the method for obtaining spectral reflectance, uses ordinary camera with multiple illuminations. Conventional model-based methods allow to recover spectral reflectance efficiently by using only a few parameters, however it requires some parameters such as power spectrum of illuminations and spectrum sensitivity of camera. In this paper, we propose an enhanced model-based spectrum recovering method without pre-measured parameters: power spectrum of illuminations and spectrum sensitivity of camera. Instead of measuring each parameters, spectral reflectance can be efficiently recovered by estimating and using the spectrum characteristic matrix which contains spectrum parameters: basis function, power spectrum of illumination, and spectrum sensitivity of camera. The spectrum characteristic matrix can be easily estimated using captured images from scenes with color checker under multiple illuminations. Additionally, we suggest fast recovering method preserving positive constraint of spectrum by nonnegative basis function of spectral reflectance. Results of our method showed accurately reconstructed spectral reflectance and fast constrained estimation with unmeasured camera and illumination. As our method could be conducted conveniently, measuring spectral reflectance is expected to be widely used.

• Journal of Photoscience
• /
• v.7 no.4
• /
• pp.139-142
• /
• 2000

To examine applicability of some optical indices from reflectance to estimate photosynthetic light use efficiency, photosynthesis, and narrow band spectral reflectance were simultaneously measured at various intensities of light with mongolian oak leaves. Narrow band of the broad-band NDVI was better than photochemical reflectance index and simple ratio to estimate photosynthetic light use efficiency in this study. Changes in spectral reflectance were detected at several wavelengths (540nm, 690nm, 740nm, and 800nm) associated with physiological status of plant leaves that could be components for new optical indices.

• Journal of the Korean Graphic Arts Communication Society
• /
• v.22 no.1
• /
• pp.9-18
• /
• 2004

Recently as color image processing to be become independent have been desired at the light source in an image processing and it have been enlarged. An image processing of the light source which is become independent means an image processing which uses a spectral reflectance information. We improved it in the spectral reflectance estimation method which uses existing 3-band image in this research that the improvement of an identity color population generation method which uses the hue angle and the processing speed improvement and introduces a labelling method. The precision of a spectral reflectance estimation appeared to the ${\Delta}E^*_{ab}$ of an average 2.7 comparing with the measurement price. The practical use possibility came to be fast and appeared a processing speed compared with existing method.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.10
• /
• pp.142-149
• /
• 2013

In general, a color of an image is represented by using red, green, and blue channels in a RGB camera system. However, only information of three channels are limited to estimate a spectral reflectance of a real scene. Because of this, the RGB camera system can not accurately represent the color. To overcome this limitation and represent an accurate color, researches to estimate the spectral reflectance by using a multi-channel camera system are being actively proceeded. Recently, a reflectance estimation method adaptively constructing a similar training set from a traditional training set according to a camera response by using a spectral similarity was introduced. However, in this method, an accuracy of the similar training set is reduced because the spectral similarity based on an average and a maximum distances was applied. In this paper, a reflectance estimation method applied a spectral similarity based on a correlation coefficient is proposed to improve the accuracy of the similar training set. Firstly, the correlation coefficient between the similar training set and the spectral reflectance obtained by Wiener estimation method is calculated. Secondly, the similar training set is constructed from the traditional training set according to the correlation coefficient. Finally, Wiener estimation method applied the similar training set is performed to estimate the spectral reflectance. To evaluate a performance of the proposed method with previous methods, experimental results are compared. As a result, the proposed method showed the best performance.

• Journal of Korea Multimedia Society
• /
• v.4 no.1
• /
• pp.37-45
• /
• 2001

The studies to estimate the surface spectral reflectance of an object have received widespread attention using the multi-spectral camera system. However, the multi-spectral camera system requires the additional color filter according to increment of the channel and system complexity is increased by multiple capture. Thus, this paper proposes an algorithm to reduce the estimation error of surface spectral reflectance with the conventional 3-band RGB camera. In the proposed method, adaptive principal components for each pixel are calculated by renewing the population of surface reflectances and the adaptive principal components can reduce estimation error of surface spectral reflectance of current pixel. To evaluate performance of the proposed estimation method, 3-band principal component analysis, 5-band wiener estimation method, and the proposed method are compared in the estimation experiment with the Macbeth Color Checker. As a result, the proposed method showed a lower mean square error between the estimated and the measured spectra compared to the conventional 3-band principal component analysis method and represented a similar or advanced estimation performance compared to the 5-band wiener method.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2000.12a
• /
• pp.49-52
• /
• 2000

The Estimation method for spectral reflectance of the object using five-band and nine-band have been developed. The five-band acquisition are required of five or three times same work for color image acquisition process. To solve the above problems, we proposed a new method that can be reconstructed spectral reflectance of object. The proposed method was to classify same hues corresponding a color stimulus, by using hue angle and chroma vector of a color stimulus. The reconstruction of spectral reflectance was examined by computer simulation, and evaluated by MSE(Mean Square Error) and color difference between the original and reconstructed spectral reflectance.

• Journal of the Korean Graphic Arts Communication Society
• /
• v.18 no.2
• /
• pp.1-12
• /
• 2000

This paper proposes a new algorithm classifing same hues in order toe estimate the spectral reflectance of object from 3 band color image information. To estimate the spectral reflectance of object, the conventional estimation methods are required of 5 or 9 band digital color values. The 5 or 9 band image acquisition systems are required of 5 or 3 times same work for color image acquisition process. To solve the above problems, we propose a new method that can be estimated spectra reflectance estimation of object. The proposed method is to classify same hues corresponding a color stimulus, by using hue angle and chroma vector of a color stimulus. The classified same hues are used as the population corresponding a color stimulus. The range of same hue is estimated by the cumulative proportional ration according to the number of basis function.