• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.266-274
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• 2007

This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on top-down machine learning and recursive error back-projection. A face is represented by a linear combination of prototypes of shape and that of texture. With the shape and texture information of each pixel in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those that of texture by solving least square minimizations. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes. In addition, a recursive error back-projection procedure is applied to improve the reconstruction accuracy of high-resolution facial image. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to reconstruct high-resolution facial images from low-resolution images captured at a distance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.38-42
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• 2002

A fast iterative solving method of fuzzy relational equation is proposed. It is derived by eliminating a redundant comparison process in the conventional iterative solving method (Pedrycz, 1983). The proposed method is applied to image reconstruction, and confirmed that the computation time is decreased to 1 / 40 with the compression rate of 0.0625. Furthermore, in order to make any initial solution converge on a reconstructed image with a good quality, a new cost function is proposed. Under the condition that the compression rate is 0.0625, it is confirmed that the root mean square error of the proposed method decreases to 27.34% and 86.27% compared with those of the conventional iterative method and a non iterative image reconstruction method, respectively.

• Journal of the Korean Institute of Telematics and Electronics
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• v.17 no.1
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• pp.23-30
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• 1980

The reconstruction problem in a low dose case requires some compromise of resolution and noise artifacts, and also some modification of filter kernels depending on the signal-to-noise ratio of projection data. In this paper, ail algorithm for the reconstruction of an image function from noisy projection data is suggested, based on minimum-mean-square error criterion. Modification of the falter kernel is made from information (statistics) obtained from the projection data. The simulation study Proves that this algorithm, based on the Wiener falter approach, provides substantially improved image with reduction of noise as well as improvement of the resolution. An approximate method was also studied which leads to the possible use of a recursive filter in the convolution process of image reconstruction.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.199-207
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• 2021

This paper deals with accurate image reconstruction of gamma camera using a coded-aperture mask based on pixel-type CsI(Tl) scintillator coupled with silicon photomultipliers (SiPMs) array. Coded-aperture imaging (CAI) system typically has a smaller effective viewing angle than Compton camera. Thus, if the position of the gamma source to be searched is out of the fully-coded field-of-view (FCFOV) region of the CAI system, artifacts can be generated when the image is reconstructed by using the conventional cross-correlation (CC) method. In this work, we propose an effective method for more accurate reconstruction in CAI considering the source distribution of partially-coded field-of-view (PCFOV) in the reconstruction in attempt to overcome this drawback. We employed an iterative algorithm based on compressed-sensing (CS) and compared the reconstruction quality with that of the CC algorithm. Both algorithms were implemented and performed a systematic Monte Carlo simulation to demonstrate the possiblilty of the proposed method. The reconstructed image qualities were quantitatively evaluated in sense of the root mean square error (RMSE) and the peak signal-to-noise ratio (PSNR). Our simulation results indicate that the proposed method provides more accurate location information of the simulated gamma source than the CC-based method.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2197-2204
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• 2015

In recent years, medical image diagnosis has growing significant momentous in the medicinal field. Brain and lung image of patient are distorted with salt and pepper noise is caused by moving the head and chest during scanning process of patients. Reconstruction of these images is a most significant field of diagnostic evaluation and is produced clearly through techniques such as linear or non-linear filtering. However, restored images are produced with smaller amount of noise reduction in the presence of huge magnitude of salt and pepper noises. To eliminate the high density of salt and pepper noises from the reproduction of images, a new efficient fuzzy based median filtering algorithm with a moderate elapsed time is proposed in this paper. Reproduction image results show enhanced performance for the proposed algorithm over other available noise reduction filtering techniques in terms of peak signal -to -noise ratio (PSNR), mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), image enhancement factor (IMF) and structural similarity (SSIM) value when tested on different medical images like magnetic resonance imaging (MRI) and computer tomography (CT) scan brain image and CT scan lung image. The introduced algorithm is switching filter that recognize the noise pixels and then corrects them by using median filter with fuzzy two-sided π- membership function for extracting the local information.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.640-644
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• 1997

This poaper descibes a method for reconstructing the impact force by inverse analysis. The inverse problem of reconstructing the impact force using experimentally measured structural responses tends to be ill-conditioned. In practical application, impact response data involve niise caused by the measurement system. We present a method to minimize the mean square error of reconstructed forcd. The agreement is very satisfactory in all the comparisons. This verifies the proposed method.

• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.817-825
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• 1997

Images reconstructed with EM algorithm have been observed to have checkerboard effects and have large distortions near edges as iterations proceed. We suggest a aimple algorithm of applying line process to the EM and Bayesian EM to reduce the distortions near edges. We show by simulation that this algorithm improves the clarity of the reconstructed image and has good properties based on root mean square error.

• Current Optics and Photonics
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• v.5 no.6
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• pp.606-616
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• 2021

A photonic integrated interferometric imaging system possesses the characteristics of small-scale, low weight, low power consumption, and better image quality. It has potential application for replacing conventional large space telescopes. In this paper, the principle of photonic integrated interferometric imaging is investigated. A novel lenslet array arrangement and lenslet pairing approach are proposed, which are helpful in improving spatial frequency coverage. For the novel lenslet array arrangement, two short interference arms were evenly distributed between two adjacent long interference arms. Each lenslet in the array would be paired twice through the novel lenslet pairing approach. Moreover, the image reconstruction model for optical interferometric imaging based on compressed sensing was established. Image simulation results show that the peak signal to noise ratio (PSNR) of the reconstructed image based on compressive sensing is about 10 dB higher than that of the direct restored image. Meanwhile, the normalized mean square error (NMSE) of the direct restored image is approximately 0.38 higher than that of the reconstructed image. Structural similarity index measure (SSIM) of the reconstructed image based on compressed sensing is about 0.33 higher than that of the direct restored image. The increased spatial frequency coverage and image reconstruction approach jointly contribute to better image quality of the photonic integrated interferometric imaging system.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.9
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• pp.143-147
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• 2016

Recently, digital tomosynthesis system (DTS) has been developed to reduce overlap using conventional X-ray and to overcome high patient dose problem using computed tomography (CT). The purpose of this study was to develop image reconstruction algorithm and to evaluate image characteristics and dose with chest digital tomosynthesis (CDT) system. Image reconstruction was used for filtered back-projection (FBP) methods and system geometry was constructed ${\pm}10^{\circ}$, ${\pm}15^{\circ}$, ${\pm}20^{\circ}$, and ${\pm}30^{\circ}$ angular range for acquiring phantom images. Image characteristics carried out root mean square error (RMSE) and signal difference-to-noise ratio (SDNR), and dose is evaluated effective dose with ${\pm}20^{\circ}$ angular range. According to the results, the phantom image with slice thickness filter has superb RMSE and SDNR, and effective dose was 0.166 mSv. In conclusion, we demonstrated usefulness of developed CDT image reconstruction algorithm and we constructed CDT basic output data with measuring effective dose.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.46-49
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• 2003

A concept of fuzzy wavelets is proposed by a fuzzification of morphological wavelets. In the proposed fuzzy wavelets, analysis and synthesis schemes can be formulated as the operations of fuzzy relational calculus. In order to perform an efficient compression and reconstruction, an alphaband is also proposed as a soft thresholding of the wavelets. In the image compression/reconstruction experiment using test images extracted Standard Image DataBAse (SIDBA), it is confirmed that the root mean square error (RMSE) of the proposed soft thresholding is decreased to 87.3％ of the conventional hard thresholding.