• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.738-747
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• 2015

It is difficult to use a recognition algorithm of an image in a foggy environment because the color and edge information is removed. One of the famous defogging algorithm is haze removal by using 'Dark Channel Prior(DCP)' which is used to predict for transmission rate using color information of an image and eliminates fog from the image. However, in case that the image has factors such as sunset or yellow dust, there is overemphasized problem on the color of certain channel after haze removal. Furthermore, in case that the image includes an object containing high RGB channel, the transmission related to this area causes a misestimated issue. In this paper, we purpose an enhanced fog elimination algorithm by using improved color normalization and haze rate revision which correct mis-estimation haze area on the basis of color information and edge information of an image. By eliminating the color distortion, we can obtain more natural clean image from the haze image.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.2
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• pp.57-62
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• 1999

Estimation of the point spread function (PSF) is one of the main research topic of image processing, because it determines the performance of the auto-focusing system. In this paper, a new algorithm for PSF estimation is proposed, and its application to image restoration is also presented. The procedure for complete realization of the auto-focusing system consists of two steps: PSF estimation based on edge classification, and image restoration using the estimated PSF. More specifically, we divide imput image into multiple small image or block, estimate unit step response and average them on the blocks which contain edge, and estimate 2-dimensional isotropic PSF from the 1 dimensional step response. Finally we obtain in-focused image by using image restoration based on the estimated PSF.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.91-102
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• 2010

It is very difficult that a previous surveillance system and vehicle detection system find objects on a limited and unstable illumination condition. This paper proposes a robust method of adaptively updating a reference background image for solving problems that are generated by the unstable illumination. The first input image is set up as the reference background image, and is divided into three block categories according to an edge component. Then a block state analysis, which uses a rate of change of the brightness, a stability, a color information, and an edge component on each block, is applied to the input image. On the reference background image, neighbourhood blocks having the same state of a updated block are merged as a block. The proposed method can generate a robust reference background image because it distinguishes a moving object area from an unstable illumination. The proposed method very efficiently updates the reference background image from the point of view of the management and the processing time. In order to demonstrate the superiority of the proposed stable manner in situation that an illumination quickly changes.

• Journal of the Korean Institute of Navigation
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• v.13 no.1
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• pp.11-20
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• 1989

Radar image data were collected through the on-line data acquisition system of A/D converter and personal computer, and the image was restorated on CRT or plotter after digital image processing of the data. The digital image processing system which was developed for this study, consisted of some kinds of software as follows : rearrangement, transformation, and enhancement of the image data in real space or frequency space by Fourier transform, edge detection of the image, compact processing, state inferential processing, and so on. Since the image of PPI radar sweeps from the center to the circumference of a circle, the image within a given period has the shape of fan. Therefore the acquired data were transformed to have the same interval as that of data in outmost concentricity. The results of various image processing methods using transformed data were better than those of the methods using original data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1503-1508
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• 2009

This study applied image processing techniques, constructed to real-time, to thermal infrared camera image. Thermal infrared image data was utilized for hot mapping, cool mapping, and rainbow mapping according to changing temperature. It was histogram image processing techniques so that detected shade contrast function of the thermal infrared image, and the thermal infrared image's edge was extracted to classification of object. Moreover, extraction of temperature from image was measured by using the image information program.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.359-371
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• 2011

Edge detection in images is an important step in image segmentation and object recognition as preprocessing for image processing. This paper presents a new edge detection using local histogram analysis based on wavelet transform. In this work, the wavelet transform uses three components (horizontal, vertical and diagonal) to find the magnitude of the gradient vector, instead of the conventional approach in which tw components are used. We compare the magnitude of the gradient vector with the threshold that is obtained from a local histogram analysis to conclude that an edge is present or not. Some experimental results for our edge detector with a Sobel, Canny, Scale Multiplication, and Mallat edge detectors on sample images are given and the performances of these edge detectors are compared in terms of quantitative and qualitative measures. Our detector performs better than the other wavelet-based detectors such as Scale Multiplication and Mallat detectors. Our edge detector also preserves a good performance even if the Sobel and Canny detector are sharply low when the images are highly corrupted.

• Journal of radiological science and technology
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• v.43 no.1
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• pp.15-21
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• 2020

This study was purpose to evaluation of Modulation Transfer Function in Measurements by using the International electrotechnical commission standard(IEC 62220-1) which were edge device each angle by using edge method. In this study was Aero(Konica, Japan) image receptor which is a indirect Flat panel detector(FPD) was used. The size of matrix 1994 × 2430 (14"× 17" inch) which performed 12 bit processing and pixel pitch is 175 ㎛. The results of shown as MTF measurements at IEC standard. The amount of data seemed reasonable and at an MTF value of 0.1 the spatial frequencies were 2.56 cycles/mm at an angle of 2.4°. MTF value of 0.5 the spatial frequencies were 1.32 cycles/mm at an angle of 2.4°. This study were to evaluate MTF by setting each angle 2.0°~2.8° degrees the most effective optimal edge angle and to suggest the quantitative methods of measuring by using IEC.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1369-1373
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• 2015

Curve subdivision interpolation reconstructs edge well with low complexity, however it lacks of ability to recover texture components, instead. While, neighbor embedding is superior in texture reconstruction. Therefore, in this paper, a novel Super Resolution technique which combines curve subdivision interpolation and neighbor embedding is proposed. First, edge region and non-edge regions are classified. Then, for edge region, the curve subdivision algorithm is used to make two polynomials derived from discrete pixels and adaptive weights are adapted for gradients of 4 different sides to make smooth edge. For non edge region, neighbor-embedding method is used to conserve texture property in original image. Consequently results show that the proposed technique conserves sharp edges and details in texture better, simultaneously.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.315-322
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• 2006

Ant Colony System(ACS) is easily applicable to the traveling salesman problem(TSP) and it has demonstrated good performance on TSP. Recently, ACS has been emerged as the useful tool for the pattern recognition, feature extraction, and edge detection. The edge detection is wifely utilized in the area of document analysis, character recognition, and face recognition. However, the conventional operator-based edge detection approaches require additional postprocessing steps for the application. In the present study, in order to overcome this shortcoming, we have proposed the new ACS-based edge detection algorithm. The experimental results indicate that this proposed algorithm has the excellent performance in terms of robustness and flexibility.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9C
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• pp.704-711
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• 2008

This paper proposes a new de-interlacing method which results in efficient visual improvement. In the proposed algorithm, the distance weight was considered and the previously developed the EDI (Edge Dependent Interpolation) algorithm and the NAL (New Adaptive Linear interpolation) algorithm were used as a basis. The do-interlacing method was divided into two main parts. First, the edge direction was found by using information of closer pixels. Then, missing pixels were interpolated along with the decided edge direction. In this paper, after predicting the edge through the EDI algorithm, missing pixels were interpolated by using the weighted distance based on the NAL algorithm. Experimental results indicate that the proposed algorithm be superior to the conventional algorithms in terms of the objective and subjective criteria.