• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.3
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• pp.173-180
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• 2003

The modified Wiener filtering method is proposed for effective noise suppression in edge region of images corrupted by additive white gaussian noise. Although the pixels classified as a edge region in the conventional Wiener filter have lots of noise components, the conventional Wiener filler cannot remove noise effectively due to the preserving of edges. To reduce noise well in edge region, we modify filter coefficients of the conventional Wiener filter The modified filter coefficients increase in noise suppression effect In edge region, while they preserve edges for strong edge region. From simulation $(256{\time}256$ size, 256 graylevel images) filtered images by the proposed method show much improved subjective image quality with some improved peak signal-to-noise ratio compared to those by the conventional Wiener filtering.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.2
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• pp.118-126
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• 2004

The modified Wiener filtering method is proposed for effective noise suppression in edge region of images corrupted by additive white gaussian noise. Although the pixels classified as a edge region in the conventional Wiener filter have lots of noise components, the conventional Wiener filter cannot remove noise effectively due to the preserving of edges. To reduce noise well in edge region, we modify filter coefficients of the conventional Wiener filter. The modified filter coefficients increase in noise suppression effect in edge region, while they preserve edges for strong edge region. From simulation (256${\times}$256 size, 256 graylevel images) filtered images by the proposed method show much improved subjective image quality with higher peak signal-to-noise ratio compared to those by the conventional Wiener filtering.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.552-562
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• 2018

With the advent of the information society, image restoration technology has aroused considerable interest. Guided image filtering is more effective in suppressing noise in homogeneous regions, but its edge-preserving property is poor. As such, the critical part of guided filtering lies in the selection of the guided image. The result of the Expected Patch Log Likelihood (EPLL) method maintains a good structure, but it is easy to produce the ladder effect in homogeneous areas. According to the complementarity of EPLL with guided filtering, we propose a method of coupling EPLL and guided filtering for image de-noising. The EPLL model is adopted to construct the guided image for the guided filtering, which can provide better structural information for the guided filtering. Meanwhile, with the secondary smoothing of guided image filtering in image homogenization areas, we can improve the noise suppression effect in those areas while reducing the ladder effect brought about by the EPLL. The experimental results show that it not only retains the excellent performance of EPLL, but also produces better visual effects and a higher peak signal-to-noise ratio by adopting the proposed method.

• Journal of Biomedical Engineering Research
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• v.17 no.4
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• pp.427-432
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• 1996

The primary purpose of port filming is to verify the treatment volume under treatment. Although the image quality with the megavoltage x-ray beam is poorer than with the diagnostic or the simulator film. This paper proposes an edge-adaptive Kalman filter for the image enhancement of port films. Suggested filtering procedure preserves edge information and eliminates edge noise and inside and outside treatment area preserving treatment boundary.

• Journal of Astronomy and Space Sciences
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• v.15 no.1
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• pp.175-182
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• 1998

Any classification process using SAR images presupposes the reduction of multiplicative speckle noise, since the variations caused by speckle make it extremely difficult to distinguish between neighboring classes within the feature space. Therefore, several adaptive filter algorithms have been developed in order to distinguish between them. These algorithms aim at the preservation of edges and single scattering peaks, and smooths homogeneous areas as much as possible. This task is rendered more difficult by the multiplicative nature of the speckle noise the signal variation depends on the signal itself. In this paper, LEE(Lee 1908) and R-LEE(Lee 1981) filters using local statistics, local mean and variance, are applied to RADARSAT SAR images. Also, a new method of speckle filtering, EPOS(Edge Preserving Optimal Speckle)(Hagg & Sties 1994) filter based on the statistical properties of speckle noise is described and applied. And then, the results of filtering SAR images with LEE, R-LEE and EPOS filters are compared with mean and median filters.

• 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.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.439-441
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• 2005

A kernel regression filter with adaptive bandwidth is developed and successfully applied to digital reactivity meter for neutron signal measurement in nuclear reactors. The purpose of this work is not only reduction of the measurement noise but also the edge preservation of the reactivity signal. The performance of the filtering algorithm is demonstrated comparing with well known smoothing methods of conventional low-pass and bilateral filters. The developed method gives satisfactory filtering performance and edge preservation capability.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.5
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• pp.726-731
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• 1986

An effective filtering algorithm which can reduce noise and preserve edges for the restoration of an image degraded by additive white Gaussian noise is presented. The algorithm proposed in this paper is an extension of Lee's algorithm modified to use local gradient information as well as local statistics. It does not require image modeling, and removes noise along the orientaiton of edges so that it does not blur the edge.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.241-244
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• 2005

Many building detection methods mainly rely on line segments extracted from aerial or satellite imagery. Building detection methods based on line segments, however, are difficult to succeed in high resolution satellite imagery such as IKONOS imagery, for most buildings in IKONOS imagery have small size of roofs with low contrast between roof and background. In this paper, we propose an efficient method to extract line segments and group them at the same time. First, edge preserving filtering is applied to the imagery to remove the noise. Second, we segment the imagery by watershed method, which collects the pixels with similar intensities to obtain homogeneous region. The boundaries of homogeneous region are not completely coincident with roof boundaries due to low contrast in the vicinity of the roof boundaries. Finally, to resolve this problem, we set up snake model with segmented region boundaries as initial snake's positions. We used a greedy algorithm to fit a snake to roof boundary. Experimental results show our method can obtain more .correct roof boundary with small size and low contrast from IKONOS imagery. Snake algorithm, building roof detection, watershed segmentation, edge-preserving filtering

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.54-58
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• 2002

Mean curvature diffusion (MCD) is a selective smoothing technique that promotes smoothing within a region instead of smoothing across boundaries. By using mean curvature diffusion, noise is eliminated and edges are preserved. In this paper, we propose methods of automatic parameter selection and implementation for the MCD model coupled to min/max flow. The algorithm has been applied to high resolution aerial images and the results show that noise is eliminated and edges are preserved after removal of noise.