• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.273-273
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• 2000

We present a new scheme to increase the performance of edge-preserving image smoothing from the parameter tuning of a Markov random field (MRF) function. The method is based on automatic control of the image smoothing-strength in MRF model ing in which an introduced parameter function is based on control of enforcing power of a discontinuity-adaptive Markov function and edge magnitude resulted from discontinuities of image intensity. Without any binary decision for the edge magnitude, adaptive control of the enforcing power with the full edge magnitude could improve the performance of discontinuity-preserving image smoothing.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.535-538
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• 2009

Speckle noise reduction for ultrasound CT image using morphological adaptive median filtering based on edge preservation is presented in this paper. Speckle noise is multiplicative feature and causes ultrasound image to degrade widely from transducer. An input image is classified into edge region and homogeneous region in preprocessing. The speckle is reduced by morphological operation on the 2D gray scale by using convolution and correlation, and edges are preserved. The adaptive median is processed to reduce an impulse noise to preserve edges. As the result, MAM of the proposed method enhances the image to about 10% in comparison with Winner filter by Edge Preservation Index and PSNR, and 10% to only adaptive median filtering.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.81-84
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• 2001

We propose a novel noise littering method based on adaptive windowing. To restore a noisy signal adaptive filtering methods have been widely researched and used. However, conventional adaptive filtering methods have a trade-off between noise suppression and edge preservation since they adopt fixed size filters. In this paper applying the adaptive windowing concept to adaptive filtering, we overcome the trade-off, The filter size is adaptively selected depending on signal statistics. The visual results of the signal and image restorations convincingly show the superior preservation of edge and detail and suppression of noise for the proposed adaptive windowed adaptive filter compared with conventional methods.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.569-571
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• 1998

In this paper, we propose a method of restoring blurred images by an edge-sensitive adaptive filter. The direction of the edge is estimated using the properties of 2-D block FFT. Reduction of blurring due to the added noise during image transfer and the focus of lens caused by shooting a fast moving object is very important. To remove this phenomenon effectively, we can use the edge information obtained by processing the blurred images. The proposed algorithm estimates both the existence and the direction of the edge. On the basis of the acquired edge direction information, we choose the appropriate edge-sensitive adaptive filter, which enables us to get better images than images obtained by methods not considering the direction of the edge. The performance of the proposed algorithm is shown in the simulation result.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.889-892
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• 2000

본 논문에서는 효과적인 De-interlacing을 위한 Edge based Median Filter와 3-Step AMPD(Adaptive Minimum Pixel Difference Filter)를 제안한다. Motion Adaptive De-interlacing 방법에서 중요한 요소인 Motion Hissing에 의한 에러를 방지하기 위해 입력 영상을 4 가지 유형으로 구분하여 각 영상에 따라 다른 임계 값을 적용하여 정확한 화소 값을 보간 하는AMPD(Adaptive Minimum Pixel Difference) Filter를 사용하며 Moving Diagonal Edge의 효과적인 보간을 위해서 방향 필터를 사용하여 Edge Map을 추출한 뒤 Edge에 따라 가변적인 후보 화소를 선택하는 Edge based Median Filter를 사용하여 성능을 향상시켰다. 또한 입력되는 영상을 움직임 영역, 정지 영역, 경계 영역으로 나누어 적응적으로 보간 하여 연산 효율을 높였다. 제안된 방법은 다양한 영상에 대한 모의실험을 통해 기존의 방법에 비해 뛰어난 성능 개선을 보였다.

• Convergence Security Journal
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• v.6 no.3
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• pp.29-35
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• 2006

In order to detect and locate edge features precisely in real images we have developed an algorithm by introducing a nonlocal differentiation of intensity profiles called adaptive directional derivative (ADD), which is evaluated independently of varying ramp widths. In this paper, we first develop the edge detector system employing the ADD and then, the performance of the algorithm is illustrated by comparing the results to those from the Canny's edge detector.

• Convergence Security Journal
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• v.7 no.3
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• pp.39-44
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• 2007

In order to detect and locate edge features precisely in real images we have developed an algorithm by introducing a nonlocal differentiation of intensity profiles called adaptive directional derivative (ADD), which is evaluated independently of varying ramp widths. In this paper, we first develop the edge detector system employing the ADD and then, the performance of the algorithm is illustrated by comparing the results to those from the Canny's edge detector.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2921-2923
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• 2000

Adaptive template filtering has been proposed recently for an enhancement of signal-to-noise ratio. In some magnetic resonance images whose gray levels have relatively small dynamic ranges, e.g., T1 imaging, however, artificial stair-like artifact is observed in edge regions. This is partially due to edge enhancement effect in such voxels that contain multiple compounds at the boundaries of tissues. The gray levels of these voxels tend to change those of near voxels that contain single compound by the adaptive filtering, which exaggerate edge discontinuities. In this paper, we propose a technique to eliminate such artifact by identifying those voxels and assigning a larger template for them. Filtered images with the proposed technique show substantial visual enhancement at the edges without degradation of peak signal-to-noise ratio compared to the original adaptive template filtering for both magnetic resonance images and phantom images

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.329-332
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• 2009

Speckle noise reduction for ultrasound CT image using morphological adaptive median filtering based on edge preservation is presented in this paper. Speckle noise is multiplicative feature and causes ultrasound image to degrade widely from transducer. An input image is classified into edge region and homogeneous region in preprocessing. The speckle is reduced by morphological operation on the 2D gray scale by using convolution and correlation, and edges are preserved. The adaptive median is processed to reduce an impulse noise. As the result the proposed method enhances the image to about 20% in comparison with Winer filter by Edge Preservation Index and PSNR.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2068-2086
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• 2011

Based on the quincunx sub-sampling grid, the New Interleaved Hierarchical INTerpolation (NIHINT) method is recognized as a superior pyramid data structure for the lossless and progressive coding of natural images. In this paper, we propose a new image interpolation algorithm, Edge Adaptive Hierarchical INTerpolation (EAHINT), for a further reduction in the entropy of interpolation errors. We compute the local variance of the causal context to model the strength of a local edge around a target pixel and then apply three statistical decision rules to classify the local edge into a strong edge, a weak edge, or a medium edge. According to these local edge types, we apply an interpolation method to the target pixel using a one-directional interpolator for a strong edge, a multi-directional adaptive weighting interpolator for a medium edge, or a non-directional static weighting linear interpolator for a weak edge. Experimental results show that the proposed algorithm achieves a better compression bit rate than the NIHINT method for lossless image coding. It is shown that the compression bit rate is much better for images that are rich in directional edges and textures. Our algorithm also shows better rate-distortion performance and visual quality for progressive image transmission.