• Title/Summary/Keyword: local contrast

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An Adaptive Histogram Equalization Based Local Technique for Contrast Preserving Image Enhancement

  • Lee, Joonwhoan;Pant, Suresh Raj;Lee, Hee-Sin
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.15 no.1
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    • pp.35-44
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    • 2015
  • The main purpose of image enhancement is to improve certain characteristics of an image to improve its visual quality. This paper proposes a method for image contrast enhancement that can be applied to both medical and natural images. The proposed algorithm is designed to achieve contrast enhancement while also preserving the local image details. To achieve this, the proposed method combines local image contrast preserving dynamic range compression and contrast limited adaptive histogram equalization (CLAHE). Global gain parameters for contrast enhancement are inadequate for preserving local image details. Therefore, in the proposed method, in order to preserve local image details, local contrast enhancement at any pixel position is performed based on the corresponding local gain parameter, which is calculated according to the current pixel neighborhood edge density. Different image quality measures are used for evaluating the performance of the proposed method. Experimental results show that the proposed method provides more information about the image details, which can help facilitate further image analysis.

Fog degree measurement using DCP based transmission and local contrast in single image (Single image에서 빛 전달량 및 local contrast를 사용한 안개량 측정 방법)

  • Lee, geun min;Kim, won ha
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2016.11a
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    • pp.176-178
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    • 2016
  • Single image를 사용하여 안개양을 측정하는 방법으로는 소실점, 지평선의 local contrast를 측정하는 방법과 DCP의 빛 전 달양을 사용하는 방법이 있다. 하지만 local contrast를 사용하는 방법은 특정한 환경에서만 사용이 가능하고 DCP는 대기의 color와 비슷한 color를 가진 물체들이 많을 경우 사용하기 어렵다는 한계가 있다. 그래서 본 논문은 영상의 빛 전달양과 Local Contrast를 사용하여 다양한 contents를 가진 single image에서 안개양을 수치화하는 새로운 방법을 제시한다. 제시하는 방법은 DCP로부터 측정한 빛 전달량으로부터 안개일 가능성이 있는 빛 전달량 지역의 면적과 해당 지역에서의 Local contrast의 분포 정도를 측정하여 DoF를 계산한다.

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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.

Application of Local Histogram and Plateau Equalization Algorithm for Contrast Enhancement of Real Time Thermal Image (실시간 열영상 대조비 개선을 위한 대역추출 및 플래토 평활화 알고리즘 적용)

  • 조흥기;김수곤;전희종
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.2
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    • pp.76-85
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    • 2004
  • In this paper, the contrast enhancement method of thermal image is proposed and it is the plateau equalization algorithm using local histogram for the real time display of infrared imagery. Through hardware implementing, its practicality and adequacy are proved. Examinations are executed to verify the effect of contrast enhancement by bright control and contrast control automatic to the plateau value in the manual mode, and that verified the effect of contrast enhancement in the automatic mode and the practicality in the real system. According to the experiment results, the proposed "the application of local histogram and plateau equalization algorithm for contrast enhancement of real time thermal image"in this dissertation is the verified method for the thermal imaging contrast enhancement.

A Tone Mapping Method by Local Contrast and Detail Enhancement for High Dynamic Range Images

  • Kim, Beom-Yong;Hwang, Bo-Hyun;Yun, Jong-Ho;Choi, Myung-Ryul
    • 한국정보디스플레이학회:학술대회논문집
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    • 2008.10a
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    • pp.741-744
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    • 2008
  • In this paper, tone mapping method by local contrast and detail enhancement for High Dynamic Range (HDR) is proposed. By applying Piecewise Dynamic Range Histogram Adjustment (PDRHA) and Detail Enhancement Volume (DEV) with decomposed layers, tone mapping is performed effectively. The experimental results show that the proposed method preserves local contrast and overall impression with naturalness of original images.

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Global Contrast Enhancement Using Block based Local Contrast Improvement (블록기반 지역 명암대비 개선을 통한 전역 명암대비 향상 기법)

  • Kim, Kwang-Hyun;Han, Young-Joon;Hahn, Hern-Soo
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.45 no.1
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    • pp.15-24
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    • 2008
  • This paper proposes a scheme of global image contrast enhancement using local contrast improvement. Methods of global image contrast enhancement redistribute the image gray level distribution using histogram equalization without considering image properties, and cause the result image to include image pixels with excessive brightness. On the other hand, methods of the block-based local image contrast enhancement have blocking artifacts and a problem of eliminating important image features during an image process to reduce them. In order to solve these problems, the proposed method executes the block-based histogram equalization on temporary images that an input image is divided into various fixed-size blocks. And then it performs the global contrast enhancement by applying the global histogram equalization functions to the original input image. Since the proposed method selects the best histogram equalization function from temporary images that are improved by the block-based local image contrast enhancement, it has the advantages of both the local and global image contrast enhancement approaches.

Spatial Contrast Enhancement using Local Statistics based on Genetic Algorithm

  • Choo, MoonWon
    • Journal of Multimedia Information System
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    • v.4 no.2
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    • pp.89-92
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    • 2017
  • This paper investigates simple gray level image enhancement technique based on Genetic Algorithms and Local Statistics. The task of GA is to adapt the parameters of local sliding masks over pixels, finding out the best parameters preserving the brightness and possibly preventing the creation of intensity artifacts in the local area of images. The algorithm is controlled by GA as to enhance the contrast and details in the images automatically according to an object fitness criterion. Results obtained in terms of subjective and objective evaluations, show the plausibility of the method suggested here.

Regional Contrast Enhancement for Local Dimming Backlight on Small-sized Mobile Display

  • Chung, Jin-Young;Kim, Ki-Doo
    • 한국정보디스플레이학회:학술대회논문집
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    • 2009.10a
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    • pp.972-974
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    • 2009
  • This paper presents smart regional contrast enhancement technique of partitioned image for local dimming backlight on small-sized mobile display to reach two goals. One is to save the power consumption, and the other to improve contrast ratio of display image. Recently new advanced method is proposed, named local dimming method, that backlight LED is positioned on backside of the display panel. So it is important to partition an image by sub blocks and then post-processing independantly. This means regional contrast enhancement. After partitioning, we compare the mean luminance(Y) value of each sub-block image with the one of original whole image. If some blocks have the mean value lower than the one of whole image, they are processed with the proposed method and others are bypassed. Simultaneously the information of the processed blocks are transferred to BLC(Backlight LED Controller). And then the supply current of each backlight LED is reduced to realize the contrast ratio enhancement and at the same time to power consumption reduction. In addition, we verify this proposed method is free from blocking artifacts.

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Shape Preserving Contrast Enhancement

  • Hwang Jae Ho
    • Proceedings of the IEEK Conference
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    • 2004.08c
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    • pp.867-871
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    • 2004
  • In this paper, a new analytic approach for shape preserving contrast enhancement is presented. Contrast enhancement is achieved by means of segmental histogram stretching modification which preserves the given image shape, not distorting the original shape. After global stretching, the image is partitioned into several level-sets according to threshold condition. The image information of each level-set is represented as typical value based on grouped differential values. The basic property is modified into common local schemes, thereby introducing the enhanced effect through extreme discrimination between subsets. The scheme is based on stretching the histogram of subsets in which the intensity gray levels between connected pixels are approximately same In spite of histogram widening, stretched by local image information, it neither creates nor destroys the original image, thereby preserving image shape and enhancing the contrast. By designing local histogram stretching operations, we can preserve the original shape of level-sets of the image, and also enhance the global intensity. Thus it can hold the main properties of both global and local image schemes, which leads to versatile applications in the field of digital epigraphy.

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Smoke Detection Method Using Local Binary Pattern Variance in RGB Contrast Imag (RGB Contrast 영상에서의 Local Binary Pattern Variance를 이용한 연기검출 방법)

  • Kim, Jung Han;Bae, Sung-Ho
    • Journal of Korea Multimedia Society
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    • v.18 no.10
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    • pp.1197-1204
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    • 2015
  • Smoke detection plays an important role for the early detection of fire. In this paper, we suggest a newly developed method that generated LBPV(Local Binary Pattern Variance)s as special feature vectors from RGB contrast images can be applied to detect smoke using SVM(Support Vector Machine). The proposed method rearranges mean value of the block from each R, G, B channel and its intensity of the mean value. Additionally, it generates RGB contrast image which indicates each RGB channel’s contrast via smoke’s achromatic color. Uniform LBPV, Rotation-Invariance LBPV, Rotation-Invariance Uniform LBPV are applied to RGB Contrast images so that it could generate feature vector from the form of LBP. It helps to distinguish between smoke and non smoke area through SVM. Experimental results show that true positive detection rate is similar but false positive detection rate has been improved, although the proposed method reduced numbers of feature vector in half comparing with the existing method with LBP and LBPV.