• Journal of Multimedia Information System
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• 제4권2호
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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.

• Transactions on Electrical and Electronic Materials
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• 제15권4호
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• pp.230-234
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• 2014

Automatic detection of disease helps medical institutions that are introducing digital images to read images rapidly and accurately, and is thus applicable to lesion diagnosis and treatment. The aim of this study was to apply a symmetry contribution algorithm to unsharp mask filter-applied MR images and propose an analysis technique to automatically recognize brain tumor and edema. We extracted the skull region and drawed outline of the skull in database of images obtained at P University Hospital and detected an axis of symmetry with cerebral characteristics. A symmetry contribution algorithm was then applied to the images around the axis of symmetry to observe intensity changes in pixels and detect disease areas. When we did not use the unsharp mask filter, a brain tumor was detected in 60 of a total of 95 MR images. The disease detection rate for the brain was 63.16%. However, when we used the unsharp mask filter, the tumor was detected in 87 of a total of 95 MR images, with a disease detection rate of 91.58%. When the unsharp mask filter was used in the pre-process stage, the disease detection rate for the brain was higher than when it was not used. We confirmed that unsharp mask filter can be used to rapidly and accurately to read many MR images stored in a database.

• 대한전자공학회논문지SP
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• 제47권5호
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• pp.145-152
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• 2010

본 논문에서는 초점 열화를 제거하기 위해서 반복적 Unsharp mask (UM) 필터를 이용한 디지털 자동초점 기법을 제안한다. 제안한 디지털 자동초점 기술은 영상열화를 추정하기 위해서 점확산함수를 추정하지 않고 단순한 필터를 사용하기 때문에 계산량이 적은 장점을 갖는다. 본 기법은 반복적 필터 구조로 영상을 복원하기 때문에 사용자의 주관적 기준 및 영상의 객관적 지표를 사용하여 필터링의 반복 회수를 제한할 수 있다. 또한 반복적 UM 기반의 영상개선 방법이 기존의 반복적 영상복원 기술과 등가임을 보인다. 마지막으로 본 논문에서 제안한 알고리듬의 성능평가를 위해서 기존의 영상복원 기반의 디지털 자동초점 기술과의 비교 실험을 수행하였고, 이를 통하여 제안한 디지털 자동초점 기법이 주관적으로나 객관적으로 우수함을 보였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.893-894
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• 2008

In this paper, we propose a sharpening approach which is based on unsharp masking through the adaptive windowing. This adaptive windowing changes the window size of the low-pass filter which is used in unsharp mask for reducing the halo artifacts.