• Journal of information and communication convergence engineering
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• v.8 no.4
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• pp.349-354
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• 2010

Moving pixel displacement detection algorithm using correlation functions for making panorama image on the continuous images is presented in this paper. The input images get from a CMOS image sensor (CIS). The camera is maintained by constant brightness and uniform sensing area in test input pattern. For simple navigation and capture image has to 70% overlapped region. A correlation rate in two image data is evaluated by using reference image with first captures, and compare image with next captures. The displacement of the two images are expressed to second order function of x, y and solved with finding the coefficient in second order function. That results in the change in the peak correlation displacement from the reference to the compare image, is moving to pixel length. The navigating error is reduced by varying the path because the error is shown in the difference of the positioning vector between the true pixel position and the navigated pixel position. The algorithm performance is evaluated to be different from the error vector to vary the navigating path grid.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1156-1161
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• 2007

Edge representing the boundary between two regions with the large briskness difference in mage includes diverse information about object. Therefore, this information has been utilized in fields such as image segmentation and object recognition. There are many kinds of edge according to duration time and the amplitude of brightness variation and edge is generally detected through the differential. Recently, in fields of image processing and computer vision, edge detection methods have been proposed to use in specific applications. Hence, in this paper the wavelet function for improved edge detection properties was proposed and detected line-edge components of images and its performance was proven through simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.8 no.3
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• pp.105-112
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• 1983

This paper discribes technique of the recursive restoration for the images degraded by linear space invariant blur and additive white Gaussian noise. The image is characterized statistically by tis mean and correlation function. An exponential autocorrelation function has been used to model neighborhood model. The vector model was used because of analytical simplicitly and capability to implement brightness correlation function. Base on the vector model, a two-dimensional discrete stochastic a 12 point neighborhood model for represeting images was developme and used the technique of moving window processing to restore blurred and noisy images without dimensionality increesing, It has been shown a 12 point neighborhood model was found to be more adequate than a 8 point pixel model to obtain optimum pixel estimated. If the image is highly correlated, it is necessary to use a large number of points in the neighborhood in order to have improvements in restoring image. It is believed that these result could be applied to a wide range of image processing problem. Because image processing thchniques normally required a 2-D linear filtering.

• The Journal of the Acoustical Society of Korea
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• v.26 no.8
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• pp.409-414
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• 2007

In spite of many studies of the acoustic field visualization by using sonoluminescence phenomena, the visualization method has not been used widely because it needs high acoustic intensity to get the luminescence intensity enough to observe. Recently, the digital camera with high resolution and big memory makes it possible to get the digital image data even though the brightness of the image is too weak to observe with naked eyes. In this study we investigated the variation of sonoluminescence intensity with the acoustic intensity from an ultrasonic transducer. From this result, the inverse function, which makes the tendency of the variation to linear, was obtained. Using the order of the inverse function, we can expect a matching function. Applying the matching function to digital image data, the distribution of the histogram could be controlled appropriately and the image from relatively weak acoustic intensity could be enhanced by the method.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.63.2-63.2
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• 2016

One of the well-known problems in the lambda cold dark matter (${\Lambda}CDM$) models is a missing satellite problem. The slope of the mass function of low mass galaxies predicted by ${\Lambda}CDM$ models is much steeper than that based on the luminosity function of dwarf galaxies in the local universe. This implies that the model prediction is an overestimate of low mass galaxies, or that the current census of dwarf galaxies in the local universe may be an underestimate of dwarf galaxies. Previous studies of galaxy luminosity functions to address this problem are based mostly on the sample of galaxies brighter than Mv ~ -10 in the nearby galaxies. In this study we try to search for ultra-faint galaxies (UFDs), which are much fainter than those in the previous studies. We use multi-field HST ACS images of M60 in the archive. M60 is a giant elliptical galaxy located in the east part of the Virgo cluster, and hosts a large population of globular clusters and UCDs. Little is known about the dwarf galaxies in this galaxy. UFDs are much fainter, much smaller, and have lower surface brightness than normal dwarf galaxies so HST images of massive galaxies are an ideal resource. We present preliminary results of this search.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.4
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• pp.672-681
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• 2017

This paper is concerned with the design methodology of face recognition system based on pose estimation. In 2-dimensional face recognition, the variations of facial pose cause the deterioration of recognition performance because object recognition is carried out by using brightness of each pixel on image. To alleviate such problem, the proposed face recognition system deals with Learning Vector Quantizatioin(LVQ) or K-Nearest Neighbor(K-NN) to estimate facial pose on image and then the images obtained from LVQ or K-NN are used as the inputs of networks such as Convolution Neural Networks(CNNs) and Radial Basis Function Neural Networks(RBFNNs). The effectiveness and efficiency of the post estimation using LVQ and K-NN as well as face recognition rate using CNNs and RBFNNs are discussed through experiments carried out by using ICPR and CMU PIE databases.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.401-408
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• 2012

There is a clear need for characterizing optical components with the growing role played by optical devices in measurement, communication, and photonics. A basic and useful measuring parameter to meet this need, especially for imaging systems, is the Modulation Transfer Function, or MTF. Over the past few decades new instrument, including the laser interferometer, the CCD camera, and the computer have revolutionized the measurement and calculation of the MTF. This has made what was tedious and involved into virtually an instantaneous measurement. We proposed a Simpson approxiamtion method to create MTF graph and illustrated real example to verify its method in this paper. This method is very useful while it is very useful because its error is very minor and small although its approximation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.20-27
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• 2007

Generally, the TFT-LCD image signal have nonuniform brightness and are composed of largely varying background signal, noise signal and abruptly changing Mura signal within Mura region. In this paper, Mura region enhancing algorithms using the proposed modified-MTF, which describes how human-visual-system's sensitivity varies in frequency domain, is proposed. The validity of the proposed algorithm was demonstrated ideal 1-dimensional signal and also then it was also tested TFT-LCD image. By the experimental results, the proposed algorithm is very effective in TFT-LCD image Mura enhancement.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.4
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• pp.287-294
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• 2008

This paper describes an implementation of a wide-range dimming controller of a LED backlight for Avionics applications such as a control display unit(CDU) and multi-function display(MFD). The digital dimming controller employing a current controlled buck converter and light sensor feedback is proposed. The proposed system provides a wide dimming control range of from 150fL to 0.05fL(3000:1) required for avionic displays. The experimental results are provided to show the control performance.

• Korean Journal of Remote Sensing
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• v.19 no.6
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• pp.479-490
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• 2003

This study proposed a modified anisotropic diffusion restoration for image classification. The anisotropic diffusion restoration uses a probabilistic model based on Markov random field, which represents geographical connectedness existing in many remotely sensed images, and restores them through an iterative diffusion processing. In every iteration, the bonding-strength coefficient associated with the spatial connectedness is adaptively estimated as a function of brightness gradient. The gradient function involves a constant called "temperature", which determines the amount of discontinuity and is continuously decreased in the iterations. In this study, the proposed method has been extensively evaluated using simulated images that were generated from various patterns. These patterns represent the types of natural and artificial land-use. The simulated images were restored by the modified anisotropic diffusion technique, and then classified by a multistage hierarchical clustering classification. The classification results were compared to them of the non-restored simulation images. The restoration with an appropriate temperature considerably reduces error in classification, especially for noisy images. This study made experiments on the satellite images remotely sensed on the Korean peninsula. The experimental results show that the proposed approach is also very effective on image classification in remote sensing.