• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1633-1649
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• 2017

In remote sensing image processing, the traditional fusion algorithm is based on the Intensity-Hue-Saturation (IHS) transformation. This method does not take into account the texture or spectrum information, spatial resolution and statistical information of the photos adequately, which leads to spectrum distortion of the image. Although traditional solutions in such application combine manifold methods, the fusion procedure is rather complicated and not suitable for practical operation. In this paper, an improved IHS transformation fusion algorithm based on the local variance weighting scheme is proposed for remote sensing images. In our proposal, firstly, the local variance of the SPOT (which comes from French "Systeme Probatoire d'Observation dela Tarre" and means "earth observing system") image is calculated by using different sliding windows. The optimal window size is then selected with the images being normalized with the optimal window local variance. Secondly, the power exponent is chosen as the mapping function, and the local variance is used to obtain the weight of the I component and match SPOT images. Then we obtain the I' component with the weight, the I component and the matched SPOT images. Finally, the final fusion image is obtained by the inverse Intensity-Hue-Saturation transformation of the I', H and S components. The proposed algorithm has been tested and compared with some other image fusion methods well known in the literature. Simulation result indicates that the proposed algorithm could obtain a superior fused image based on quantitative fusion evaluation indices.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3803-3810
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• 2022

OpenMC is a community-driven open-source Monte Carlo neutron and photon transport simulation code. The Weight Window Mesh (WWM) function and an automatic Global Variance Reduction (GVR) method was recently developed and implemented in a developmental branch of OpenMC. This WWM function and GVR method broaden OpenMC's usage in general purposes deep penetration shielding calculations. However, the Local Variance Reduction (LVR) method, which suits the source-detector problem, is still missing in OpenMC. In this work, the Weight Window Generator (WWG) function has been developed and benchmarked for the same branch. This WWG function allows OpenMC to generate the WWM for the source-detector problem on its own. Single-material cases with varying shielding and sources were used to benchmark the WWG function and investigate how to set up the particle histories utilized in WWG-run and WWM-run. Results show that there is a maximum improvement of WWM generated by WWG. Based on the above results, instructions on determining the particle histories utilized in WWG-run and WWM-run for optimal computation efficiency are given and tested with a few multi-material cases. These benchmarks demonstrate the ability of the OpenMC WWG function and the above instructions for the source-detector problem. This developmental branch will be released and merged into the main distribution in the future.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.285-294
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• 2004

Median Filters in the Signal Processing have been most widely used and have demonstrated the most strongest effects. This paper proposes the Adaptive Median Filters by using noise detection. The basic algorithm of the proposed filters is to determine whether noise or not by the each noise judgement standards, and then take the Median Filter if it satisfies the conditions as a result of judgement and returns to the original image(No Filters) if not. This paper presented Noise Detection by Local Variance and Local Central Variance for noise judgement, compared and analyzed the features and performance of existing [5]∼[10] Filters. Filter improved on the result of executing the existing filters at the same condition and showed the effects over that when it was judged with naked eyes. Accordingly, the Adaptive Median Filters by Local Variance and Local Central Variance was proven to have reinforced edge preservation ability and have the strong features for removing the Impulse Noise of the Median Filter.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.77-87
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• 2001

Some asymptotic results on the local likelihood density estimator of Copas(1995) are derived when the locally parametric model has several parameters. It turns out that it has the same asymptotic mean squared error as that of Hjort and Jones(1996).

• Asian-Australasian Journal of Animal Sciences
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• v.6 no.3
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• pp.433-440
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• 1993

Means and standard errors of 285 Taiwan's local chicken and 429 Single Comb White Leghorn pullets at 35 wk of age were: egg weight (g) $48.3{\pm}0.3$, $54.6{\pm}0.3$, shell index $73.39{\pm}0.26$, $73.20{\pm}0.18$, shell color $15.23{\pm}0.40$, $0.88{\pm}0.27$, shell whiteness $72.61{\pm}0.57$, $90.00{\pm}0.35$, shell strength ($kg/cm^2$) $3.77{\pm}0.07$, $3.35{\pm}0.05$, shell thickness (mm) $0.38{\pm}0.003$, $0.38{\pm}0.002$, Haugh units $85.26{\pm}0.50$, $91.81{\pm}0.38$ and yolk percent (%) $30.17{\pm}0.18$, $27.32{\pm}0.16$ respectively. Theestimated heritabiliities of Taiwan's local chicken based on sire and dam components of variance were as follows: egg weight 0.20, shell index 0.1, shell color 0.87, shell whiteness 0.79, shell strength 0.37, shell thickness 0.14, Haugh units 0.24 and yolk percent 0.16. Genetic correlations based on sire and dam components of variance and covariance were also estimated. Generically, the shell index was positively correlated with egg weight, shell strength and yolk percent, and egg weight was negatively correlated with shell thickness, Haugh unit and yolk percent.

• Asian-Australasian Journal of Animal Sciences
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• v.8 no.3
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• pp.295-300
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• 1995

Data from purebred and crossbred cattle involving Holstein and the Local breed in Bangladesh were used to estimate the genetic effects on average daily milk yield and birth weight A total of 877 records on average daily milk yield for 4 types of breed groups and a total of 418 records on birth weight for 5 breed groups were analyzed. Two different methods were applied in this study; the least squares analysis of variance approach and the linear regression approach. Breed group effects were highly significant for both average daily milk yield and birth weight. The result showed that straightbred Holstein produced the highest milk yield and the 7/8 crosses ranked highest in birth weight For the two traits, the additive breed effect was highly significant, whereas the individual heterosis effect was not significant. Furthermore, this study showed a negative maternal heterosis for average daily milk yields and a positive maternal heterosis for birth weight Comparing the breed least squares means obtained from the linear regression approach revealed that straightbred Holstein produced the highest average milk yield and the 3/4 crosses were predicted to have the largest birth weight. It is indicated that the linear regression approach can adequately separate the genetic component of performance, estimate unknown crossbreeding parameters and predict unknown performance of crosses which are not include in the original data.

• Plant Resources
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• v.4 no.1
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• pp.31-35
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• 2001

Major characteristics of new Waesungri maize inbred line has multi-tiller and ears: five to six tillers and seven to eight ears per plant and flowering date of Waesungri was delayed about 18 and 24 days compared to Mo17 U.S line and IK$_4$ Korean local lines, respectively. Number of ears, fresh and dry weight per plant were significantly different among all tested hybrids including Waesungri/Sinkihong hybrid under different planting times and densities. Especially, both fresh and dry weight of IK$_1$/FR140//Waesungri F$_1$hybrid were significantly higher at high planting density. In kernel weight per unit area, Wnesungri/Sinkihong hybrid was high at high density and IK$_1$/FR140//Waesungri hybrid was high at low planting density. As results of analysis of variance, flowering date was shown a significantly different both planting times and varieties, while other characters including stem height were shown very variable in interactions with enviromental factors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.629-635
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• 2017

In this paper, we proposed a nonlinear synthesis filter for noise reduction to reduce the effects of Gaussian noise and impulse noise. When the centralization of the local mask is judged to be Gaussian noise by the noise judgment, the weight value of the weight filter are applied differently according to the spatial weight filter and the pixel change by using the sample variance in the local mask. And if it is determined as the impulse noise, we proposed an algorithm that applies different weights of local histogram weight filter and standard median filter according to noise density of mask. In order to evaluate the performance of the proposed filter algorithm, we used PSNR(peak signal to noise ratio) and compared existing methods and proposed filter algorithm in the mixed noise environment with Gaussian noise, impulsive noise, and two noises mixed.

• The Journal of the Acoustical Society of Korea
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• v.24 no.1
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• pp.1-10
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• 2005

This paper presents a wideband LPA (local polynomial approximation) beamforming algorithm that is appropriate for wideband moving sources. The Proposed wideband LPA algorithm adopts STMV (steered minimum variance) method that utilizes a steered covariance matrix obtained from multiple frequency components in one data snapshot, instead of multiple data snapshots in one frequency bin. The wideband LPA cost function is formed using STMV weight vector. The Proposed algorithm searches for the instantaneous DOA and angular velocity that maximize the wideband LPA cost function. resulting in a higher resolution performance than that of a DS LPA beamforming algorithm. Several simulations using artificial data and sea trial data are used to demonstrate the performance of the Proposed algorithm.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.825-826
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• 2008

Focusing is the principal factor that decides the image quality. In the low illuminance condition, captured images with a digital camera usually blurred because the autofocus system of the camera fail to detect the in-focus position. The failure of focusing is due to thermal noise in the captured image. In this paper, we propose a new focus detection algorithm. The proposed algorithm use the new focusing index which is weighted sum of the high-frequency energy and mid-frequency energy. The weight is determined by the local variance of the image. The proposed algorithm performs stable focusing detection with in the low illuminance condition.