• Title/Summary/Keyword: image contrast

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Stroke Width-Based Contrast Feature for Document Image Binarization

  • Van, Le Thi Khue;Lee, Gueesang
    • Journal of Information Processing Systems
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    • v.10 no.1
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    • pp.55-68
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    • 2014
  • Automatic segmentation of foreground text from the background in degraded document images is very much essential for the smooth reading of the document content and recognition tasks by machine. In this paper, we present a novel approach to the binarization of degraded document images. The proposed method uses a new local contrast feature extracted based on the stroke width of text. First, a pre-processing method is carried out for noise removal. Text boundary detection is then performed on the image constructed from the contrast feature. Then local estimation follows to extract text from the background. Finally, a refinement procedure is applied to the binarized image as a post-processing step to improve the quality of the final results. Experiments and comparisons of extracting text from degraded handwriting and machine-printed document image against some well-known binarization algorithms demonstrate the effectiveness of the proposed method.

Contrast Enhanced Tone Mapping Operator for High Dynamic Range Image Based on Guided Image Filter

  • Li, Xing;Wee, Seungwoo;Jeong, Jechang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2018.06a
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    • pp.59-62
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    • 2018
  • In this paper, we propose a contrast enhancement algorithm using guided image filter (GIF). The GIF is used to divide an HDR image into a base layer and a detail layer. The energy scale of base layer determinate the darkness and brightness of the image. However, the detail information in the base layer is difficult to be displayed because of the high brightness and clusters of low brightness. We propose a contrast enhancement method by adjusting the gray level of base layer by subtracting the mean value of itself. It is combined with the detail layer to preserve the detail information. Experiment results show that the proposed algorithm has better performance in detail preservation and contrast enhancement.

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Local contrast and Transmission Based Fog Degree Measurement in Single Image (Local Contrast와 빛 전달량 기반 Single Image의 안개 정도 측정 방법)

  • Lee, Geun-min;Kim, Wonha
    • Journal of Broadcast Engineering
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    • v.22 no.3
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    • pp.375-380
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    • 2017
  • This paper has proposed a single image based fog degree quantification method by measuring both transmission and local contrast. The proposed method estimates the foggy expected regions from transmission, and then assesses the size of regions of which transmission values are foggy expected ones and the range of local contrast value on such regions. Compared with fog degree gauged by the scattering coefficient measurement sensor, the proposed method quantifies the fog degree with more than 95% accuracy for images containing various objects and environments. We also developed a technique that measures the local contrast values in process of measuring transmission values. So, the proposed method does not increase complexity compared to the existing transmission method.

A new contrast ratio measurement method using image patterns

  • Choi, Dong-Wook;Yang, Sun-A;Bae, Jae-Woo;Lee, Seung-Bae;Chung, Ho-Kyoon
    • Journal of Information Display
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    • v.12 no.2
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    • pp.85-87
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    • 2011
  • The contrast ratio is one of the most important performance parameters for display devices. The general method of measuring the contrast ratio is to determine the ratio of the full-screen white pattern to the full-screen black pattern, according to the Video Electronics Standards Association standard. Real TV images seldom have these images, however, and the conventional method does not reflect the true performance of the display in actual use. In this paper, a new contrast ratio measurement method that uses image patterns is proposed, to demonstrate that active matrix organic light-emitting diode TVs have a higher contrast than LED (LCD) TVs.

Oral contrast media for computed tomography of canine pancreas

  • Choi, Jihye;Chang, Jinhwa;Oh, Sunkyoung;Yoon, Junghee
    • Korean Journal of Veterinary Research
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    • v.51 no.2
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    • pp.165-169
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    • 2011
  • Barium suspension, oral iodine contrast medium and water were applied in eight dogs to evaluate (1) distension of gastrointestinal tract, (2) the effect of the oral contrast media on the identification of the pancreas from surrounding organs, and (3) image quality and the presence of artifacts in canine pancreas computed tomography (CT) images. Oral iodine contrast medium, gastrografin, produced significant artifacts that deteriorated the CT images of the pancreas. The use of water did not provide the fullness of the gastrointestinal lumens. Barium suspension was effective for the identification of the pancreas from the surrounding gastrointestinal tract, without significantly increasing image noise. Barium suspension can be used as an optimal contrast medium that will not cause an adverse effect on the pancreatic density and image quality.

A Modified HE Technique to Enhance Image Contrast for Scaled Image on Small-sized Mobile Display (휴대단말기용 소형 디스플레이의 영상 컨트라스트 향상을 위한 변형된 HE 기법 연구)

  • Chung, Jin-Young;Hossen, Monir;Jeong, Kyung-Hoon;Kang, Dong-Wook;Kim, Ki-Doo
    • Proceedings of the KIEE Conference
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    • 2008.10b
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    • pp.137-138
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    • 2008
  • This paper proposes the modified image contrast enhancement technique for small-sized display of mobile handset. Sample images are user interface images, in which scaled up wVGA($800{\times}480$) from qVGA($320{\times}240$) that we can see easily in mobile handset. The display size of mobile handset is relatively small, so the goal of this paper is to simplify image contrast enhancement algorithm based on conventional HE (Histogram Equalization) algorithm and improve computational effectiveness to minimize power consumption in real hardware IC. In this paper, we adopt HE technique, which is classical and widely used for image contrast enhancement. At first, the input frame image is partitioned to temporal sub-frames and then analyzes gray level histogram of each sub-frame. In case that the analyzed histogram of some sub-frames deviates so much from reference level (it means that the sub-frame image components consist of too bright ones or dark ones), apply DHE(Dynamic Histogram Equalization) algorithm. In the other case, apply classical Histogram Linearization (or Global HE) algorithm. Also we compare the HE technique with gamma LUT (Look-Up Table) method, which is known as the simplest technique to enhance image contrast.

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The Study of the Image and Positioning according to Stripe Pattern and Clothing Style (스트라이프 문양과 의복스타일에 따른 이미지 차이와 포지셔닝 연구)

  • Moon, Ju-Young
    • Fashion & Textile Research Journal
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    • v.12 no.1
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    • pp.1-9
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    • 2010
  • A purpose of this study was to find out how the casual and formal style clothes of stripe pattern giving variety by pattern direction, pattern width, and contrast coloration have an effect on image of wearers. 432 stimuli were made and 2,800 testee evaluated them using semantic differential scale. As a result, five image dimensions were drawn as a factor of attractiveness, activeness, gracefulness, visibility, and tenderness. In consequence of analysing the image difference by stripe pattern and clothing style, the stripe pattern and clothing style affect image presentation as a significant clue. And besides, as a result of positioning stimuli by image, pattern direction, coloration, and tone combination were important clues that decide image. Consequently, clothing style, stripe pattern, and contrast coloration were made clear as an efficient parameter in image presentation of clothing wearers.

A Versatile Medical Image Enhancement Algorithm Based on Wavelet Transform

  • Sharma, Renu;Jain, Madhu
    • Journal of Information Processing Systems
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    • v.17 no.6
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    • pp.1170-1178
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    • 2021
  • This paper proposed a versatile algorithm based on a dual-tree complex wavelet transform for intensifying the visual aspect of medical images. First, the decomposition of the input image into a high sub-band and low-sub-band image is done. Further, to improve the resolution of the resulting image, the high sub-band image is interpolated using Lanczos interpolation. Also, contrast enhancement is performed by singular value decomposition (SVD). Finally, the image reconstruction is achieved by using an inverse wavelet transform. Then, the Gaussian filter will improve the visual quality of the image. We have collected images from the hospital and the internet for quantitative and qualitative analysis. These images act as a reference image for comparing the effectiveness of the proposed algorithm with the existing state-of-the-art. We have divided the proposed algorithm into several stages: preprocessing, contrast enhancement, resolution enhancement, and visual quality enhancement. Both analyses show the proposed algorithm's effectiveness compared to existing methods.

Contrast Enhancement Algorithm for Backlight Images using by Linear MSR (선형 MSR을 이용한 역광 영상의 명암비 향상 알고리즘)

  • Kim, Beom-Yong;Hwang, Bo-Hyun;Choi, Myung-Ryul
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.62 no.2
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    • pp.90-94
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    • 2013
  • In this paper, we propose a new algorithm to improve the contrast ratio, to preserve information of bright regions and to maintain the color of backlight image that appears with a great relative contrast. Backlight images of the natural environment have characteristics for difference of local brightness; the overall image contrast improvement is not easy. To improve the contrast of the backlight images, MSR (Multi-Scale Retinex) algorithm using the existing multi-scale Gaussian filter is applied. However, existing multi-scale Gaussian filter involves color distortion and information loss of bright regions due to excessive contrast enhancement and noise because of the brightness improvement of dark regions. Moreover, it also increases computational complexity due to the use of multi-scale Gaussian filter. In order to solve these problems, a linear MSR is performed that reduces the amount of computation from the HSV color space preventing the color distortion and information loss due to excessive contrast enhancement. It can also remove the noise of the dark regions which is occurred due to the improved contrast through edge preserving filter. Through experimental evaluation of the average color difference comparison of CIELAB color space and the visual assessment, we have confirmed excellent performance of the proposed algorithm compared to conventional MSR algorithm.

An Adaptive Histogram Redistribution Algorithm Based on Area Ratio of Sub-Histogram for Contrast Enhancement (명암비 향상을 위한 서브-히스토그램 면적비 기반의 적응형 히스토그램 재분배 알고리즘)

  • Park, Dong-Min;Choi, Myung-Ruyl
    • The KIPS Transactions:PartB
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    • v.16B no.4
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    • pp.263-270
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    • 2009
  • Histogram Equalization (HE) is a very popular technique for enhancing the contrast of an image. HE stretches the dynamic range of an image using the cumulative distribution function of a given input image, therefore improving its contrast. However, HE has a well-known problem : when HE is applied for the contrast enhancement, there is a significant change in brightness. To resolve this problem, we propose An Adaptive Contrast Enhancement Algorithm using Subhistogram Area-Ratioed Histogram Redistribution, a new method that helps reduce excessive contrast enhancement. This proposed algorithm redistributes the dynamic range of an input image using its mean luminance value and the ratio of sub-histogram area. Experimental results show that by this redistribution, the significant change in brightness is reduced effectively and the output image is able to preserve the naturalness of an original image even if it has a poor histogram distribution.