• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.2
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• pp.376-381
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• 2009

The image data compression, recognition, restoration, etc. are parts of the digital image processing technology. In the process by various devices, noises would be made. Because the noise could damage the image, we use the image filter to preserve the original image from the noise. The image filter used in digital image process basically has a two-dimensional structure. There an two methods of creating the filter - One is reiterating one dimension and the other is using an indivisible two-dimension image filter. The image filter is being widely used along with one-dimension filter according to each noise, and various median filters are being used to remove the impulse noise. In this paper, I suggested a powerful modified median filter, and compared with conventional filters for objective verification.

• ETRI Journal
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• v.28 no.1
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• pp.51-58
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• 2006

In this paper, we propose a method of applying a lifting-based wavelet domain e-median filter (LBWDEMF) for image restoration. LBWDEMF helps in reducing the number of computations. An e-median filter is a type of modified median filter that processes each pixel of the output of a standard median filter in a binary manner, keeping the output of the median filter unchanged or replacing it with the original pixel value. Binary decision-making is controlled by comparing the absolute difference of the median filter output and the original image to a preset threshold. In addition, the advantage of LBWDEMF is that probabilities of encountering root images are spread over sub-band images, and therefore the e-median filter is unlikely to encounter root images at an early stage of iterations and generates a better result as iteration increases. The proposed method transforms an image into the wavelet domain using lifting-based wavelet filters, then applies an e-median filter in the wavelet domain, transforms the result into the spatial domain, and finally goes through one spatial domain e-median filter to produce the final restored image. Moreover, in order to validate the effectiveness of the proposed method we compare the result obtained using the proposed method to those using a spatial domain median filter (SDMF), spatial domain e-median filter (SDEMF), and wavelet thresholding method. Experimental results show that the proposed method is superior to SDMF, SDEMF, and wavelet thresholding in terms of image restoration.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1387-1390
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• 1997

In this paper we propose a novel way to restore degraded image using wavelet transform & filterbank. First, we devide a degraded image into 4-suband images using UDWT(Undecimated Wavelet Transform), and then use a proper CLS (Constrained Least Square) filter in each subband. Using a proper CLS filter ineach subband, we can save high grequency components of original image. We reconstruct a restored image from the downsampled subband images using wavelet tansform. Even though there is a trade-off between ISNR and calculation loads, we reduce the calculation loads by using wavelet transform in reconstruction with a negligible degradatiion in ISNR.

• Journal of Multimedia Information System
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• v.4 no.2
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• pp.65-73
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• 2017

This paper proposes a method to improve the image quality by designing Unsharp Mask Filter (UMF) based on Retinex theory which controls the frequency pass characteristics adaptively. Conventional unsharp masking technique uses blurring image to emphasize sharpness of image. Unsharp Masking(UM) adjusts the original image and sigma to obtain a high frequency component to be emphasized by the difference between the blurred image and the high frequency component to the original image, thereby improving the contrast ratio of the image. In this paper, we design a Unsharp Mask Filter(UMF) that can process the contrast ratio improvement method of Unsharp Masking(UM) technique with one filtering. We adaptively process the contrast ratio improvement using Unsharp Mask Filter(UMF). We propose a method based on Retinex theory for adaptive processing. For adaptive filtering, we control the weights of Unsharp Mask Filter(UMF) based on the human visual system and output more effective results.

• Korean Journal of Digital Imaging in Medicine
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• v.14 no.2
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• pp.47-56
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• 2012

Amount of radiation exposure by seeing through fluoroscopy examination while is many patient exposure administration and unprepared misgovernment be. In this study, abdominal fluoroscopy during the scan, the dose and image quality change according to the use of grid and added filter optimized by measuring the test condition is proposed. Uses seeing through fluoroscopy examination equipment of Image Intensifier of Easy Diagnost Eleva (Philips), under tube type and uses Human phantom and measures average area dose according to grid insertion existence and nonexistence and added filter kind change. Measure sum of 29 organ dose and effective dose through PCXMC imagination simulation program and image J program through noise, SNR, image distortion was measured. Resolution, sharpness, and analyzed using the MTF curves. Fluorography the grid to insert the filter thickness and thickening and increased the average area dose and organ doses and effective dose. In the case of spot examination, when inserted grid, average area dose and organ dose and effective dose increased. Filter thickens the average area dose decreased, but the organ doses and effective dose were increased when use 0.2mmCu+1mmAl filter, decreased slightly. Noise and SNR measurements without inserting the gird, if you do not use the added filter was the lowest and when measure the distortion, 0.1mmCu+1mmAl filter was no difference of image quality in case insert grid was judged that when did not use occasion added filter that do not use grid, difference of image quality does not exist. Did not show a big difference, according to the grid and uses of the added filter sharpness, and resolution. Patient dose increases with factors that reduce the quality of the image so reckless grid and the use of the added filter when abdominal fluoroscopy examination should be cautious in using.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.1
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• pp.193-204
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• 1997

In this research we propose the design of the Order Statistic-Adaptive Weighted Average Hybrid(OS-AWAH) filter which can suppress noise from the corrupted image sequence effectively while preserving the image structure. The proposed filter combines the desirable properties of the order static based spatial filter which can preserve the image structure while reducing noise and the adaptive weighted average based temporal filter which can adapt the filtering weights according to the amount of motion without motion estimation. Performance characteristics of the OS-AWAH filter in noisy sequences containing moving step edges are investigated throuth computer simulations and compared with the median based filters such as 3-D WM(weighted median) filter, MMF (multistage median filter), ADCWM(adaptive directional center weighted median) filter. The visual evaluations are also carried out by applyin gthe filters to the real images. The statistical analysis and experimental reslts show that the OS-AWAH filter is effective in preserving image structures while suppressing noise effectively without motion compensation preprocessing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1393-1398
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• 2004

Image is degraded by several causes such as the process of acquisition, storage and transmission. To restore those images, many researches have been continued. Centrally methods to restore degraded image by AWGN(additive white gaussian noise) a.e mean filter and wiener filter. Especially, mean filter is superior in noise reduction of area that is a small change of luminosity. But mean filter brings about the effect smoothing edge components of the image, because it does'nt consider characteristics of the image. So in this paper we propose an image restoration method compounding respective images adding established weights, after filtering with mean filter and powerful wiener filter in both improvement of contrast and preservation of edge components.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.329-334
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• 2005

Most people are using a Color-CCD-Camera in other to acquire a color image. But we are getting a color image with the Monochrome-CCD-Camera equipped for Rotation-Color-Filter in front of the camera lens. The Monochrome CCD Camera has some advantages such as the low price. In addition Rotation-Color-Filter's design is very simple. So we can make this structure easily and economically. In this paper, we described how to make a color image from Monocrome-Camera and correcting color well.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.693-701
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• 2011

Image registration is an essential process to analyze the time series of satellite images for the purpose of image fusion and change detection. The Mutual Information (MI) is commonly used as similarity measure for image registration because of its robustness to noise. Due to the radiometric differences, it is not easy to apply MI to multi-temporal satellite images using directly the pixel intensity. Image features for MI are more abundantly obtained by employing a Gabor filter which varies adaptively with the filter characteristics such as filter size, frequency and orientation for each pixel. In this paper we employed Bidirectional Gabor Filter Energy (BGFE) defined by Gabor filter features and applied the BGFE to similarity measure calculation as an image feature for MI. The experiment results show that the proposed method is more robust than the conventional MI method combined with intensity or gradient magnitude.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.27-33
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• 2018

In this paper, we propose an efficient edge preserving smoothing filter for Infrared image that can reduce noise while preserving edge information. Infrared images suffer from low signal-to-noise ratio, low edge detail information and low contrast. So, detail enhancement and noise reduction play crucial roles in infrared image processing. We first apply a guided image filter as a local analysis. After the filtering process, we optimization globally using relativity of guided image filter. Our method outperforms the previous methods in removing the noise while preserving edge information and detail enhancement.