• 한국컴퓨터정보학회논문지
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• 제23권12호
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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.

• 한국통신학회논문지
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• 제36권11C호
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• pp.662-672
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• 2011

본 논문은 새로운 경계선 보존 알고리즘을 이용하여 블록화 현상을 제거하는 디블로킹 필터와 HD해상도의 실시간 영상처리가 가능한 디블로킹 필터의 VLSI구조를 제안한다. 기존의 블록 분류 기반의 접근 방법과 달리 제안된 알고리즘은 픽셀 분류 기반 접근을 사용한다. 또한 제안된 경계선 보존 맵은 픽셀을 경계선 영역과 평탄 영역으로 분류하며, 블록화 현상 제거에 사용되는 오프셋 필터와 경계선 보존 필터의 기반이 된다. 이를 바탕으로 제안된 디블로킹 필터의 VLSI구조는 고연산량 처리를 위하여 블록 전체에 파이프라인 기법을 적용하였다. 또한 블록 버퍼를 위한 메모리 절감 구조는 메모리의 사용을 최적화 시킨다. 본 필터는 VHDL을 이용한 설계를 통하여 CycloneII FPGA상에서 구현된 구조의 동작을 검증 후, Synopsys의 Design Compiler와 ANAM 0.25 ${\mu}m$ CMOS cell library로 합성하여 칩으로 구현하였을 때의 성능을 예측하였다. 제안된 알고리즘의 실험 결과는 세밀한 영상성분을 보존하면서 효과적으로 블록화 현상을 제거하며, 픽셀 분류 기반에서 제안된 알고리즘은 블록 분류 기반보다 PSNR 성능이 우수함을 보였다.

• ETRI Journal
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• 제32권3호
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• pp.380-389
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• 2010

This paper presents a new edge-protection algorithm and its very large scale integration (VLSI) architecture for block artifact reduction. Unlike previous approaches using block classification, our algorithm utilizes pixel classification to categorize each pixel into one of two classes, namely smooth region and edge region, which are described by the edge-protection maps. Based on these maps, a two-step adaptive filter which includes offset filtering and edge-preserving filtering is used to remove block artifacts. A pipelined VLSI architecture of the proposed deblocking algorithm for HD video processing is also presented in this paper. A memory-reduced architecture for a block buffer is used to optimize memory usage. The architecture of the proposed deblocking filter is verified on FPGA Cyclone II and implemented using the ANAM 0.25 ${\mu}m$ CMOS cell library. Our experimental results show that our proposed algorithm effectively reduces block artifacts while preserving the details. The PSNR performance of our algorithm using pixel classification is better than that of previous algorithms using block classification.

• 한국멀티미디어학회논문지
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• 제18권10호
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• pp.1164-1171
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• 2015

The edge preserving method is important for image storage and geometric transformation. In this paper, we propose a new edge preserving method using HOG-Guide filter for image segmentation. In our approach, we extract edge information using gradient histogram to set HOG guide line. Then, we use HOG guide line to smooth image. With two to four iterations of smoothing operations, we finally obtain desirable edge preserved image. Our experimental results showed good performances showing that our proposed method is better than other methods.

• 디지털산업정보학회논문지
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• 제8권3호
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• pp.41-48
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• 2012

In this paper, we propose a method of edge detection for noisy image. The proposed method uses a progressive filter for noise reduction and a Sobel operator for edge detection. The progressive filter combines a median filter and a modified rational filter. The proposed method for noise reduction adjusts rational filter direction according to an edge in the image which is obtained by median filtering. Our method effectively attenuates the noise while preserving the image details. Edge detection is performed by a Sobel operator. This operator can be implemented by integer operation and is therefore relatively fast. Our proposed method not only preserves edge, but also reduces noise in uniform region. Thus, edge detection is well performed. Our proposed method could improve results using further developed Sobel operator. Experimental results show that our proposed method has better edge detection with correct positions than those by existing median and rational filtering methods for noisy image.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.434-436
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• 1992

In this paper, we propose a new multilevel nonlinear filter for simultaneous edge detection and noise suppression, which we call a order statistic-median hybrid(OMH) filler. The median-related filters cause an edge shift in the presence of an impulse near the edge. The proposed filter reduces such edge shifting while suppressing impulsive as well as nonimpulsive noise. We show that at the noisy edge point the OMH filter is substantially superior to the median filter, the $\alpha$-TM filter and the STM filter[I] in two respects: (a) the output bias error and (b) the output mean square error. Test results confirm that the OMH filter is robust in preserving sharp edges, inhibiting edge shifting, and suppressing a wide variety of noise. The structure for the OMH filter integrated circuit is also described.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권3호
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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.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권2호
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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.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.159-162
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• 2008

This paper presents a modified mean curvature diffusion filter to smooth speckle noise in images. Mean curvature diffusion filter has already shown good results in reducing noise in images while preserving fine details. In the mean curvature diffusion, the rate of smoothing is controlled by the local value of the diffusion coefficient chosen to be a function of the local image gradient magnitude. In this paper, the diffusion coefficient is modified to be controlled adaptively by local image surface slope and heterogeneity. The local surface slope contributes to preserving details (e.g.edges) in image and the local surface heterogeneity helps the smoothing filter consider the amount of noise in both edge and non-edge area. The proposed filter's performance is demonstrated by quantitative experiments using speckle noised aerial image and TerraSAR-X satellite image.

• ETRI Journal
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• 제34권4호
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• pp.564-571
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• 2012

This paper presents an algorithm for removing high-density impulsive noise that generates some serious distortions in edge regions of an image. Although many works have been presented to reduce edge distortions, these existing methods cannot sufficiently restore distorted edges in images with large amounts of impulsive noise. To solve this problem, this paper proposes a method using connected lines extracted from a binarized image, which segments an image into uniform and edge regions. For uniform regions, the existing simple adaptive median filter is applied to remove impulsive noise, and, for edge regions, a prediction filter and a line-weighted median filter using the connected lines are proposed. Simulation results show that the proposed method provides much better performance in restoring distorted edges than existing methods provide. When noise content is more than 20 percent, existing algorithms result in severe edge distortions, while the proposed algorithm can reconstruct edge regions similar to those of the original image.