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Yohei Saika,Masahiro Nakagawa 제어로봇시스템학회 2017 제어로봇시스템학회 국제학술대회 논문집 Vol.2017 No.10
By making use of environmental quantities, such as temperature and relative humidity, we search optimal conditions on thermal index called as the temperature-humidity index (THI) at each sampling point and power consumption due to air conditioning, both of which are estimated by repeating the Bayesian inference using the EAP estimation with an increase in the ratio of the coefficient of the model prior as to that of the likelihood. Then, we estimate static property of the Bayesian inference and dynamic property of the iterative method by making use of numerical calculations for several cases. Numerical results show that the iterative method succeeds in searching the optimal conditions on the environmental variables, if we increase the ratio up to its optimum respective of the choice of observed variables. These results are confirmed by the mean-field theory for the full-connected model.
Yohei Saika,Kenta Morimoto 제어로봇시스템학회 2012 제어로봇시스템학회 국제학술대회 논문집 Vol.2012 No.10
We studied performance of a generalized MAP estimation which was regarded as the maximizer of the posterior marginal (MPM) estimate for image reconstruction via multiple halftone images for a set of grayscale images generated by an assumed true prior and a 256-grayscale standard image. By making use of numerical simulations for those images, we clarified that performance of the generalized MAP estimation is improved with the increase in the number of the halftone images for image reconstruction, if we tune parameter scheduling appropriately. Also, we found that the present method reconstructs original images more accurately than the conventional MAP estimation and the MPM estimate.
Probabilistic Modeling to Inverse Halftoning based on Super Resolution
Yohei Saika,Ken Okamoto,Fumiya Matsubara 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10
On the basis of the Bayesian inference using the maximizer of the posterior marginal (MPM) estimate, we formulate the problem of inverse halftoning via the framework of super resolution for the organized dither method. Then, the Monte Carlo simulation for a set of the snapshots of the Q-Ising model clarifies that this method achieves optimal performance under the Bayes-optimal condition and that the Bayes-optimal solution reconstructs more accurately than the MAP estimate. Then, we find that the upper bound of the mean square error is inversely proportional to the number of halftone image in the procedure of inverse halftoning. Then, these results obtained by the Monte Carlo simulations are qualitatively confirmed by the analytical estimate using the infinite-range model. Further, we find that the present method is effective even for realistic images and however that false contour appears in reconstructed images, if we utilize a small number of the halftone images in the procedure of inverse halftoning.
Yohei Saika,Naoyuki Tahara,Tetsuya Yamasaki 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
In order to reconstruct a grayscale image from a noisy corrupted halftone image obtained by the conventional dither method, we construct a method of image restoration using the ε-filter, the discriminant analysis method and the generalized statistical smoothing. Then, using the numerical simulation for a 256-level standard image “enna” we clarify that the present method restores the gray-level image with higher image quality than the conventional method, if we appropriately tune the parameters, and that the edges of the original image are restored by the present method more accurately than other conventional method.
Yohei Saika,Shouta Akiyama,Hiroki Sakaematsu 제어로봇시스템학회 2013 제어로봇시스템학회 국제학술대회 논문집 Vol.2013 No.10
We investigated the Bayesian inferences using the maximize a posteriori (MAP) estimation for the problem of phase unwrapping in remote sensing using the synthetic aperture radar (SAR) interferometry. Then, in order to clarify performance of the Bayesian inference estimate, we carried out Monte Carlo simulation for a set of wave-fronts generated by an assumed true prior. Then, we clarified that optimal performance was achieved under the Bayes-optimal condition within statistical uncertainty. Then, we clarified that the present method was effective even for an artificial wave-front in remote sensing due to SAR interferometry. Also, we found that the Bayesian inference via the conjugate gradient method to derive the MAP solution for this problem. Using the numerical simulation for the wave-front, we found that the MAP estimation using the conjugate gradient method was effective for phase unwrapping as well as the MPM estimate approximately.
Image Restoration from Corrupted Halftone Image Using the Statistical Mechanical Iterative Method
Yohei Saika,Naoyuki Tahara,Tetsuya Yamasaki 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In order to reconstruct a grayscale image from a noisy halftone image converted by the dither method, weconstruct a method of image restoration using the ??-filter and the statistical mechanical iterative method due to the Betheapproximation established in statistical physics to approximate the thermodynamics of magnetic materials. Then, usingthe numerical simulation for a 256-level standard image “Lena” with 512??512 pixels, we clarify that our method issuccessful in image restoration more accurately than the conventional filter, if we set the parameters appropriately.
Super Resolution via Generalized Statistical Smoothing
Yohei Saika,Fumiya Matsubara,Kenta Morimoto 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10
We constructed a technique to reconstruct a high-resolution original image using multiple low-resolution corrupted images for the framework of the reconstruction-based super-resolution utilizing image registration via the correlation method, resolution transformation via the bi-cubic method and noise reduction via the generalized statistical smoothing (GSS). Using numerical simulation for 256-grayscale standard images, we clarified that the present method achieves optimal performance for the reconstruction-based super-resolution, if we appropriately set the parameter for generalized parameter scheduling and threshold for edge enhancement in the GSS for noise reduction. Also, we found that the present method reconstructs an original image more accurately than that of the method using the correlation method, the bi-cubic method and the conventional filter, such as the average and Gaussian filter.
Performance of Generalized Statistical Smoothing to Inverse halftoning
Yohei Saika,Ken Okamoto 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10
We construct a method of inverse halftoning for a halftone version of a grayscale image converted by the error diffusion method via the Floyd-Steinberg kernel by making use of the generalized statistical smoothing which is constructed by introducing both edge enhancement procedure and generalized parameter scheduling into the statistical smoothing originally proposed by Wong. Then, in order to clarify the performance of the present method, we numerically estimate the mean square error and the mean square error between original and reconstructed images modulated by the MTF function of the human vision system. Using numerical simulations for several 256-level standard images, we clarify that the optimal performance is realized by introducing the edge enhancement and the generalized parameter scheduling, if we tune parameters appropriately. Then, we find that the present method reconstructs original images with high image quality, if we introduce the appropriate models both for the edge enhancement procedure and the generalized parameter scheduling.
Yohei Saika,Masahiro Nakagawa 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10
On the basis of the mean-field theory established in statistical physics we investigate the Bayesian inference using the the expected a posterior (EAP) estimation for predicting a set of environmental variables which realize comfortable environments due to air conditioner. In this method, the posterior probability is estimated using the model prior which realizes the thermal comfort via the temperature-humidity index around the optimal value and the likelihood which expresses expressing transition probability from each comfortable state to realistic one. Then, using the mean-field theory, we find that the present method predicts the variables which approximates the optimal values of the THI at sampling points using the air conditioner power consumption of air conditioner, if we use the parameters appropriately. Further, from the results of the parameter dependence both of the THI and power consumption due to air conditioner. These results were quantitatively confirmed by numerical calculations for several realistic cases.