• Title/Summary/Keyword: Histogram

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An Advanced Contrast Enhancement Using Partially Overlapped Sub-Block Histogram Equalization (서브블록 히스토그램 등화기법을 이용한 개선된 콘트래스트 강화 알고리즘)

  • Kim, Joung-Youn;Kim, Lee-Sup;Hwang, Seung-Ho
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.12
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    • pp.58-66
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    • 1999
  • In this paper, an advanced histogram equalization algorithm for contrast enhancement is presented. Histogram equalization is the most popular algorithm. Global histogram equalization is simple and fast, but its contrast enhancement power is relatively low. Local histogram equalization, on the other hand, can enhance overall contrast more effectively, but the complexity of computation required is very high. In this paper, a low pass filter type mask is used to get a sub-block histogram equalization function to more simply produce the high contrast. The low pass filter type mask is realized by partially overlapped sub-block histogram equalization (POSHE). With the proposed method. the computation overhead is reduced by a factor of about one hundred compared to that of local histogram equalization while still achieving high contrast.

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Histogram Equalization based on Differential Compression for Image Contrast Enhancement (영상의 명암대비 향상을 위한 차별적 압축 방법 기반의 히스토그램 평활화)

  • Lee, Jae-Won;Hong, Sung-Hoon
    • Journal of Broadcast Engineering
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    • v.19 no.1
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    • pp.96-108
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    • 2014
  • In case of contrast of the image enhancement by using the conventional histogram equalization, over-enhancement, false contouring and distortion such as the details disappearance of the image occurs due to the excessive brightness change. Especially, these distortion appears when the brightness distribution is concentrated in a particular brightness level. In order to solve these problems, improved histogram equalization methods to transform the input histogram by clipping using threshold have been proposed, but contrast enhancement effect is reduced because it does not consider the characteristics of the input image's histogram to apply the same threshold for the entire histogram, and unnatural image is obtained because it does not retain the characteristics of the image. In this paper, to solve the problems of existing methods, we propose new equalization method that suppress excessive brightness changes by applying to the differential compression according to the histogram frequency, and maintain the characteristics of the input image. In addition, we propose a more effectively method to improve contrast by controlling the strength of the compression ratio depending on the characteristics of the input image.

Image Histogram Equalization Using Flexible Logistic Transformation Function (유연한 로지스틱 변환함수를 이용한 영상의 히스토그램 평활화)

  • Cho, Yong-Hyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.6
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    • pp.787-795
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    • 2009
  • This paper presents a histogram equalization based on the logistic function for enhancing the quality of images. The histogram equalization is a simple and effective spatial processing method that it enhances the quality by adjusting the brightness of image. The logistic function that is a nonlinear transformation function is applied to adaptively enhance the brightness of the image according to its intensity level frequency. We propose a flexible and asymmetrical logistic function by only using the intensity level with maximum frequency and the maximum intensity level in an histogram, and the total number of pixels. The proposed function excludes both the computation load of an exponential function and the heuristic setting of an optimal parameter values in the traditional logistic function. The proposed method has been applied for equalizing many images with a different resolution and histogram distribution. The experimental results show that the proposed method has the superior enhancement performances and the faster equalizing speed compared with the traditional histogram equalization and the adaptively modified histogram equalization, respectively. And the proposed histogram equalization can be used in various multimedia systems in real-time.

Histogram Matching Algorithm for Content-Based Dnage Retrieval (내용기반 영상검색을 위한 히스토그램 매칭 알고리즘)

  • You, Kang-Soo;Yoo, Gi-Hyoung;Kwak, Hoon-Sung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.1C
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    • pp.45-52
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    • 2008
  • In this paper, we describe the Perceptually Weighted Histogram(PWH) and the Gaussian Weighted Histogram Intersection(GWHI) algorithms. These algorithms are able to provide positive results in image retrieval. But these histogram methods alter the histogram of an image by using particular lighting conditions. Even two pictures with little differences in lighting are not easily matched. Therefore, we propose that the Histogram Matching Algorithm(HMA) is able to overcome the problem of an image being changed by the intensity or color in the image retrieval. The proposed algorithm is insensitive to changes in the lighting. From the experiment results, the proposed algorithm can achieve up to 32% and up to 30% more recall than the PWH and GWHI algorithms, respectively. Also, it can achieve up to 38% and up to 34% more precision than PWH and GWHI, respectively Therefore, with our experiments, we are able to show that the proposed algorithm shows limited variation to changes in lighting.

Efficient Contrast Enhancement Using Histogram Specification (히스토그램 명세화를 이용한 효율적인 영상 대비 향상)

  • Kim, Young-Ro;Park, Hyun-Sang
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.12
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    • pp.5127-5133
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    • 2010
  • In this paper, an efficient contrast enhancement algorithm using histogram specification is proposed. Histogram equalization and its modified methods have been effective techniques for contrast enhancement. However, they often result in excessive contrast enhancement. Besides conventional histogram specification also has a problem to get the desired histogram. We propose a method that utilizes a simple high frequency filter to get the desired histogram. The proposed technique not only produces better visual results than conventional contrast enhancement techniques, but is also adaptively adjusted to the statistical characteristics of the image.

Similar Image Retrieval using Color Histogram and Edge Histogram Descriptor (컬러 히스토그램과 에지 히스토그램 디스크립터를 이용한 영상 검색 기법)

  • Jo, Min-Hyuk;Lee, Sang-Geol;Cha, Eui-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.332-335
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    • 2013
  • In this paper, we propose an image retrieval method using an EHD (Edge Histogram Descriptor) of MPEG-7 and the color histogram. The EHD algorithm can be used to collect the gradient of edge distribution and to find a similar image. However, if you only search the edge gradient without considering the image color, the color shows a weakness. In order to overcome this problem, we use the color histogram and extract the feature to determine whether a similar image. The proposed method shows that the weakness of existing EHD can be overcome by using the color histogram.

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Magnetic Resonance Brain Image Contrast Enhancement Using Histogram Equalization Techniques (히스토그램 평형 기법을 이용한 자기 공명 두뇌 영상 콘트라스트 향상)

  • Ullah, Zahid;Lee, Su-Hyun
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.01a
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    • pp.83-86
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    • 2019
  • Histogram equalization is extensively used for image contrast enhancement in various applications due to its effectiveness and its modest functions. In image research, image enhancement is one of the most significant and arduous technique. The image enhancement aim is to improve the visual appearance of an image. Different kinds of images such as satellite images, medical images, aerial images are affected from noise and poor contrast. So it is important to remove the noise and improve the contrast of the image. Therefore, for this purpose, we apply a median filter on MR image as the median filter remove the noise and preserve the edges effectively. After applying median filter on MR image we have used intensity transformation function on the filtered image to increase the contrast of the image. Than applied the histogram equalization (HE) technique on the filtered image. The simple histogram equalization technique over enhances the brightness of the image due to which the important information can be lost. Therefore, adaptive histogram equalization (AHE) and contrast limited histogram equalization (CLAHE) techniques are used to enhance the image without losing any information.

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An Experimental Study of Image Thresholding Based on Refined Histogram using Distinction Neighborhood Metrics

  • Sengee, Nyamlkhagva;Purevsuren, Dalaijargal;tumurbaatar, Tserennadmid
    • Journal of Multimedia Information System
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    • v.9 no.2
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    • pp.87-92
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    • 2022
  • In this study, we aimed to illustrate that the thresholding method gives different results when tested on the original and the refined histograms. We use the global thresholding method, the well-known image segmentation method for separating objects and background from the image, and the refined histogram is created by the neighborhood distinction metric. If the original histogram of an image has some large bins which occupy the most density of whole intensity distribution, it is a problem for global methods such as segmentation and contrast enhancement. We refined the histogram to overcome the big bin problem in which sub-bins are created from big bins based on distinction metric. We suggest the refined histogram for preprocessing of thresholding in order to reduce the big bin problem. In the test, we use Otsu and median-based thresholding techniques and experimental results prove that their results on the refined histograms are more effective compared with the original ones.

Image Retrieval Using the Fusion of Spatial Histogram and Wavelet Moments (공간 히스토그램과 웨이브릿 모멘트의 융합에 의한 영상검색)

  • 서상용;손재곤;김남철
    • Proceedings of the IEEK Conference
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    • 2000.06d
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    • pp.11-14
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    • 2000
  • We present an image retrieval method that improves retrieval rate by using the fusion of histogram and wavelet moment features. The key idea is that images similar to a query image are selected in DB by using the wavelet moment features. Then the result images are retrieved from the selected images by using histogram method. In order to evaluate the performance of the proposed method, we use Brodatz texture database, MPEG-7 T1 database and Corel Draw photo. Experimental result shows that the proposed method is better than each of histogram method and wavelet moment method.

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Image Retrieval using Fast Wavelet Histogram and Color Information (고속 웨이블렛 히스토그램과 색상정보를 이용한 영상검색)

  • 김주현;이배호
    • Proceedings of the IEEK Conference
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    • 2000.06d
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    • pp.194-197
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    • 2000
  • Wavelet transform used for content-based image retrieval has good performance in texture image. Image features for content-based image retrieval are color, texture, and shape. In this paper, we use color feature extracted from HSI color space known as most similar vision system to human vision system and texture feature extracted from wavelet histogram which has multiresolution property. Proposed method is compared with HSI color histogram method and wavelet histogram method. It is shown better performance.

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