• Journal of Ocean Engineering and Technology
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• v.35 no.3
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• pp.183-190
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• 2021

Tomographic particle image velocimetry (PIV) is a widely used method that measures a three-dimensional (3D) flow field by reconstructing camera images into voxel images. In 3D measurements, the setting and calibration of the camera's mapping function significantly impact the obtained results. In this study, a camera self-calibration technique is applied to tomographic PIV to reduce the occurrence of errors arising from such functions. The measured 3D particles are superimposed on the image to create a disparity map. Camera self-calibration is performed by reflecting the error of the disparity map to the center value of the particles. Vortex ring synthetic images are generated and the developed algorithm is applied. The optimal result is obtained by applying self-calibration once when the center error is less than 1 pixel and by applying self-calibration 2-3 times when it was more than 1 pixel; the maximum recovery ratio is 96%. Further self-correlation did not improve the results. The algorithm is evaluated by performing an actual rotational flow experiment, and the optimal result was obtained when self-calibration was applied once, as shown in the virtual image result. Therefore, the developed algorithm is expected to be utilized for the performance improvement of 3D flow measurements.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.43.1-43.1
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• 2019

In this study, we apply a deep learning model to denoising solar magnetograms. For this, we design a model based on conditional generative adversarial network, which is one of the deep learning algorithms, for the image-to-image translation from a single magnetogram to a denoised magnetogram. For the single magnetogram, we use SDO/HMI line-of-sight magnetograms at the center of solar disk. For the denoised magnetogram, we make 21-frame-stacked magnetograms at the center of solar disk considering solar rotation. We train a model using 7004 paris of the single and denoised magnetograms from 2013 January to 2013 October and test the model using 1432 pairs from 2013 November to 2013 December. Our results from this study are as follows. First, our model successfully denoise SDO/HMI magnetograms and the denoised magnetograms from our model are similar to the stacked magnetograms. Second, the average pixel-to-pixel correlation coefficient value between denoised magnetograms from our model and stacked magnetogrmas is larger than 0.93. Third, the average noise level of denoised magnetograms from our model is greatly reduced from 10.29 G to 3.89 G, and it is consistent with or smaller than that of stacked magnetograms 4.11 G. Our results can be applied to many scientific field in which the integration of many frames are used to improve the signal-to-noise ratio.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.4
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• pp.318-324
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• 2017

We introduced a stereo camera on the aircraft to detect flight objects and to estimate the 3D position of them. The Saliency map algorithm based on PCT was proposed to detect a small object between clouds, and then we processed a stereo matching algorithm to find out the disparity between the left and right camera. In order to extract accurate disparity, cost aggregation region was used as a variable region to adapt to detection object. In this paper, we use the detection result as the cost aggregation region. In order to extract more precise disparity, sub-pixel interpolation is used to extract float type-disparity at sub-pixel level. We also proposed a method to estimate the spatial position of an object by using camera parameters. It is expected that it can be applied to image - based object detection and collision avoidance system of autonomous aircraft in the future.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.5
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• pp.382-388
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• 2016

When Flat Panel Display (FPD) is made with backlight module, such as LED TV, it inherently suffers from the non-uniform backlight luminance problem that results in un-even brightness distribution throughout the TV screen. If the luminance of each pixel location of a TV screen as a function of the driving voltage can be measured, it can be used to compensate the non-uniformity of the backlight module. We use a carefully calibrated imaging system to take pictures of a TV screen at different levels of brightness and generate the compensation functions for the driving circuitry to correct the luminance level at each pixel location. Making use of the fact that the luminance of the screen is normally brightest at around the center of the screen and gradually decreases toward the border of the screen, the luminance of the whole TV screen is approximated by a mathematical function of the pixel locations. The parameters of the function are computed in the least square sense by the values of both the pixel luminance sent from the driving circuit and the grayscale value measured from the image taken by the imaging system. To justify the correction system, a simple second order polynomial function is used to approximate the luminance across the screen. When the driving circuit voltage is corrected according to the measured function, the variance of the screen luminance is reduced to one tenth of the one measured from the un-corrected TV screen.

• Current Optics and Photonics
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• v.1 no.2
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• pp.143-149
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• 2017

LED arrays with pixel numbers of $3{\times}3$, $4{\times}4$, and $5{\times}5$ have been studied in this paper in order to enhance the optical output power and decrease heat dissipation of an AlGaInP-based light emitting diode display device (pixel size of $280{\times}280{\mu}m$) fabricated by micro-opto-electro-mechanical systems. Simulation results showed that the thermal resistances of the $3{\times}3$, $4{\times}4$, $5{\times}5$ arrays were $52^{\circ}C/W$, $69.7^{\circ}C/W$, and $84.3^{\circ}C/W$. The junction temperature was calculated by the peak wavelength shift method, which showed that the maximum value appears at the center pixel due to thermal crosstalk from neighboring pixels. The central temperature would be minimized with $40{\mu}m$ pixel pitch and $150{\mu}m$ substrate thickness as calculated by thermal modeling using finite element analysis. The modeling can be used to optimize parameters of highly integrated AlGaInP-based LED arrays fabricated by micro-opto-electro-mechanical systems technology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.2
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• pp.394-400
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• 2016

Currently, with the rapid development of the digital age, multimedia-related image devices become popular. However image deterioration is generated by multiple causes during the transmission process, with typical example of salt and pepper noise. When the noise of high density is added, existing methods are deteriorated in the characteristics of removal noise. After judging the noise condition to remove the salt and pepper noise, if the center pixel is the non-noise pixel, it is replaced with the original pixel. On the other hand, if it is the noise pixel, algorithm is suggested by the study, where the histogram of the corrupted image and the median filters are used. And for objective judgment, the proposed algorithm was compared with existing methods and PSNR(peak signal to noise ratio) was used as judgment standard. As the result of the simulation, The proposed algorithm shows a high PSNR of 32.57[dB] for Lena images that had been damaged of a high density salt and pepper noise(P=60%), Compared to the existing CWMF, A-TMF and AWMF there were improvements by 21.67[dB], 18.07[dB], and 20.13[dB], respectively.

• 한국정보디스플레이학회:학술대회논문집
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• 2005.07a
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• pp.368-370
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• 2005

High energy-efficiency TFT-LCD supporting a good image quality is developed with Data Rendering Innovation Matrix Technology. The innovative matrix consists of octal sub-pixels and sub-pixel rendering technology enhanced the light efficiency; up to 30%, and reduces the number of column drivers for the same resolution by a third.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.167-170
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• 2005

Recently, filtering methods for attenuating noise while preserving image details are in progress actively. And SM(standard median) filter showed a great performance for noise removal in impulse noise environment but, it caused edge cancellation error. So, variable methods that modified SM(standard median) filter have been proposed, and CWM(center weighted median) filter is representative. Also, there are several methods to improve the efficiency based on min/max operation in term of preserving detail and filtering speed. In this paper, we managed a pixel corrupted by impulsive noise using min/max value of the surrounding band enclosing a pixel, and compared the efficiency with exiting methods in the simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3401-3420
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• 2018

Pixel expansion and contrast are two major performance parameters for visual cryptography scheme (VCS), which is a type of secret image sharing. Random Grid (RG) is an alternative approach to solve the pixel expansion problem. Chen and Tsao proposed the first (k, n) RG-based VCS, and then Guo et al., Wu et al., Shyu, and Yan et al. significantly improved the contrast in recent years. However, the investigations on improving the contrast of threshold RG-based VCS are not sufficient. In this paper, we develop a contrast-improved algorithm for (k, n) RG-based VCS. Theoretical analysis and experimental results demonstrate that the proposed algorithm outperformers the previous threshold algorithms with better visual quality and a higher accuracy of contrast.

• Proceedings of the IEEK Conference
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• summer
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• pp.447-450
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• 2004

This paper proposes remotely sensed image classification method by fuzzy c-means clustering algorithm using average intra-cluster distance. The average intra-cluster distance acquires an average of the vector set belong to each cluster and proportionates to its size and density. We perform classification according to pixel's membership grade by cluster center of fuzzy c-means clustering using the mean-values of training data about each class. Fuzzy c-means algorithm considered membership degree for inter-cluster of each class. And then, we validate degree of overlap between clusters. A pixel which has a high degree of overlap applies to the maximum likelihood classification method. Finally, we decide category by comparing with fuzzy membership degree and likelihood rate. The proposed method is applied to IKONOS remote sensing satellite image for the verifying test.