• 제목/요약/키워드: Local contrast enhancement

검색결과 87건 처리시간 0.021초

Attention-based for Multiscale Fusion Underwater Image Enhancement

  • Huang, Zhixiong;Li, Jinjiang;Hua, Zhen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권2호
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    • pp.544-564
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    • 2022
  • Underwater images often suffer from color distortion, blurring and low contrast, which is caused by the propagation of light in the underwater environment being affected by the two processes: absorption and scattering. To cope with the poor quality of underwater images, this paper proposes a multiscale fusion underwater image enhancement method based on channel attention mechanism and local binary pattern (LBP). The network consists of three modules: feature aggregation, image reconstruction and LBP enhancement. The feature aggregation module aggregates feature information at different scales of the image, and the image reconstruction module restores the output features to high-quality underwater images. The network also introduces channel attention mechanism to make the network pay more attention to the channels containing important information. The detail information is protected by real-time superposition with feature information. Experimental results demonstrate that the method in this paper produces results with correct colors and complete details, and outperforms existing methods in quantitative metrics.

흉부 엑스레이 영상을 위한 화질 개선 알고리즘 (Image Quality Enhancement for Chest X-ray images)

  • 박소연;송병철
    • 전자공학회논문지
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    • 제52권10호
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    • pp.97-107
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    • 2015
  • 디지털 엑스레이 기기로부터 처음 획득된 엑스레이 영상은 데이터 범위가 일반 영상에 비해 넓고 밝기 레벨이 고르지 못하다. 특히 흉부 엑스레이 영상의 경우 다양한 이유로 촬영하기 때문에 갈비뼈와 혈관, 척추 뼈 등 특성이 다른 모든 부위들을 자연스럽게 개선할 필요가 있다. 이러한 엑스레이 영상의 경우 일반 영상과 특성이 다르기 때문에 기존의 화질 개선 알고리즘으로는 진단에 적합한 화질을 얻을 수 없다. 따라서 본 논문은 특정 밝기에 밀집된 정보들의 히스토그램 범위를 확장시키고, 주파수 대역 별 가중치 조절을 통한 선명도 개선 및 고주파 성분의 특성을 이용한 영상 융합 기법을 통해 최종적으로 영상의 대비를 적절하게 개선하는 흉부 엑스레이 영상용 화질 개선 방법을 제안한다. 또한 기존의 기법들과 비교하여 흉부 엑스레이 영상을 보다 자연스럽게 개선하는 것을 확인하고 discrete entropy와 saturation을 통해 정량적 평과 결과를 보인다.

Image Feature Detection and Contrast Enhancement Algorithms Based on Statistical Tests

  • Kim, Yeong-Hwa;Nam, Ji-Ho
    • Journal of the Korean Data and Information Science Society
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    • 제18권2호
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    • pp.385-399
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    • 2007
  • In many image processing applications, a random noise makes some trouble since most video enhancement functions produce visual artifacts if a priori of the noise is incorrect. The basic difficulty is that the noise and the signal are difficult to be distinguished. Typical unsharp masking (UM) enhances the visual appearances of images, but it also amplifies the noise components of the image. Hence, the applications of a UM are limited when noises are presented. This paper proposed statistical algorithms based on parametric and nonparametric tests to adaptively enhance the image feature and the noise combining while applying UM. With the proposed algorithm, it is made possible to enhance the local contrast of an image without amplifying the noise.

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신호 방향을 고려한 영상 화질 개선 (Image Enhancement Using Signal Direction)

  • 신동인;김원하
    • 대한전자공학회논문지SP
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    • 제49권4호
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    • pp.32-39
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    • 2012
  • 본 논문에서는 DCT 영역에서 영상 신호의 방향과 변화의 크기에 따라 신호의 에너지를 조절하여 영상의 화질을 안정적으로 개선하는 방법을 개발한다. 이를 위하여 DCT 영역에서 영상 신호의 gradient를 측정하여 gradient의 방향과 크기로 영상의 sharpness, 국부 명암대비, 전역 명암대비에 해당하는 주파수 성분들의 에너지를 조절한다. 제안하는 기법은 기존의 기법들과 비교하여 블록화, 울림화 현상 발생과 잡음 증폭 없이 가장 우수한 화질로 향상시키는 것을 실험으로 보여준다.

디지털 맘모그램을 위한 라플라시안 피라미드에서 대비 척도를 이용한 대비 향상 방법 (A Contrast Enhancement Method using the Contrast Measure in the Laplacian Pyramid for Digital Mammogram)

  • 전금상;이원창;김상희
    • 융합신호처리학회논문지
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    • 제15권2호
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    • pp.24-29
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    • 2014
  • X-선 유방촬영술은 유방암의 조기발견을 위해 가장 일반적으로 이용되고 있다. 유방암의 조기 발견과 진단의 효율성을 증가시키기 위하여 많은 영상향상 방법들이 연구개발 되었다. 본 논문은 디지털 맘모그램을 위하여 라플라시안 피라미드에서 대비척도를 이용한 다중 스케일 대비 향상 방법을 제안한다. 제안한 방법은 입력 영상을 가우시안 피라미드와 라플라시안 피라미드로 분해하고, 분해된 다해상도 영상의 피라미드 계수들은 저주파수 성분들과 고주파수 성분들의 비율로 대역 제한된 국부 대비척도를 정의한다. 대비 향상을 위하여 정의된 대비척도를 이용하여 분해된 피라미드 계수들을 수정하고, 수정된 계수들로 피라미드 복원 과정을 거처 최종 향상된 영상을 얻는다. 제안된 방법의 성능은 실험을 통하여 기존 방법들과 향상결과를 비교하고, 대비 측정 알고리즘을 이용한 정량적인 평가결과에서 우수한 성능을 확인하였다.

Blending of Contrast Enhancement Techniques for Underwater Images

  • Abin, Deepa;Thepade, Sudeep D.;Maitre, Amulya R.
    • International Journal of Computer Science & Network Security
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    • 제22권1호
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    • pp.1-6
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    • 2022
  • Exploration has always been an instinct of humans, and underwater life is as fascinating as it seems. So, for studying flora and fauna below water, there is a need for high-quality images. However, the underwater images tend to be of impaired quality due to various factors, which calls for improved and enhanced underwater images. There are various Histogram Equalization (HE) based techniques which could aid in solving these issues. Classifying the HE methods broadly, there is Global Histogram Equalization (GHE), Mean Brightness Preserving HE (MBPHE), Bin Modified HE (BMHE), and Local HE (LHE). Each of these HE extensions have their own pros and cons and thus, by considering them we have considered BBHE, CLAHE, BPDHE, BPDFHE, and DSIHE enhancement algorithms, which are based on Mean Brightness Preserving HE and Local HE, for this study. The performance is evaluated with non-reference performance measures like Entropy, UCIQE, UICM, and UIQM. In this study, we apply the enhancement algorithms on 300 images from the UIEB benchmark dataset and then apply the techniques of cascading fusion on the best-performing algorithms.

적응형 언샤프 마스킹을 위한 지역적 밝기 기반의 가중치 맵 생성 기법 (A Weight Map Based on the Local Brightness Method for Adaptive Unsharp Masking)

  • 황태훈;김진헌
    • 한국멀티미디어학회논문지
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    • 제21권8호
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    • pp.821-828
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    • 2018
  • Image Enhancement is used in various applications. Among them, unsharp masking methods can improve the contrast with a simple operation. However, it has problems of noise enhancement and halo effect caused by the use of a single filter. To solve this problems, adaptive processing using multi-scale and bilinear filters is being studied. These methods are effective for improving the halo effect, but it require a lot of calculation time. In this paper, we want to simplify adaptive filtering by generating a weight map based on local brightness. This weight map enables adaptive processing that eliminates the halo effect through a single multiplication operation. Through experiments, we confirmed the suppression of the halo effect through the result image of the proposed algorithm and existing algorithm.

시각특성을 고려한 디지털 흉부 X-선 영상의 적응적 향상기법 (Adaptive image enhancement technique considering visual perception property in digital chest radiography)

  • 김종효;이충웅;민병구;한만청
    • 전자공학회논문지B
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    • 제31B권8호
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    • pp.160-171
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    • 1994
  • The wide dynamic range and severely attenuated contrast in mediastinal area appearing in typical chest radiographs have often caused difficulties in effective visualization and diagnosis of lung diseases. This paper proposes a new adaptive image enhancement technique which potentially solves this problem and there by improves observer performance through image processing. In the proposed method image processing is applied to the chest radiograph with different processing parameters for the lung field and mediastinum adaptively since there are much differences in anatomical and imaging properties between these two regions. To achieve this the chest radiograph is divided into the lung and mediastinum by gray level thresholding using the cumulative histogram and the dynamic range compression and local contrast enhancement are carried out selectively in the mediastinal region. Thereafter a gray scale transformation is performed considering the JND(just noticeable difference) characteristic for effective image displa. The processed images showed apparenty improved contrast in mediastinum and maintained moderate brightness in the lung field. No artifact could be observed. In the visibility evaluation experiment with 5 radiologists the processed images with better visibility was observed for the 5 important anatomical structures in the thorax.

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퍼지 논리를 이용한 흐린 영상의 콘트라스트 향상 (Contrast Enhancement of Blurred Images Using Fuzzy Logic Concepts)

  • 박중조;김경민;박귀태
    • 전자공학회논문지B
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    • 제31B권8호
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    • pp.181-191
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    • 1994
  • A new method for enhancing blurred images using fuzzy logic concepts is proposed. Blurred images contain blurred boundaries which make it difficult to detect edges and segment areas in images. In order to sharpen blurred edges local contrast information of an image and erosion/dilation properties of local min/max operations are used in which local min/max operations are fuzzy logic operations. so that given images are transformed to fuzzy images and then these operations are applied on them. In this method the sharpening operation can be iteratively applied to the image to get better deblurring effect and gray-scale "salt-and-pepper" noises are suppressed. the efficiency of our algorithm is demonstrated through experimental results obtained with artificially-made blurred images and real blurred images.

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화질 향상을 위한 색역 사상 (Gamut Mapping Algorithm for Image Quality Enhancement)

  • 김재철;허태욱;조맹섭
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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    • pp.251-254
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    • 2002
  • Currently many devices reproduce electronic images in a variety of ways. However, the colors that are reproduced are different from the original color due to the differences in the gamut between devices. In this paper, a gamut mapping method utilizing a simultaneous mapping function and a lightness rescaling is proposed. This method enhance the local-color characteristics and lightness contrast. The experimental result shows that the overall contrast and the colorfulness were increased.

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