• Title/Summary/Keyword: Histogram enhancement

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An Image Enhancement Algorithm based on Color Constancy and Histogram Equalization using Edge Region (색채 항상성 방법과 경계 영역 기반 히스토그램 평활화 방법을 이용한 영상의 화질 향상 방법)

  • Cho, Dong-Chan;Kang, Hyung-Sub;Kim, Whoi-Yul
    • Journal of Broadcast Engineering
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    • v.15 no.3
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    • pp.332-345
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    • 2010
  • A unified image enhancement method is proposed for high-resolution image which based on color constancy and histogram equalization using edge region. To speed up the method, smaller image is used when parameters of color constancy and histogram equalization are determined. In the color constancy process, nth-derivative of gaussian is applied to x and y axis separately in order to estimate the color of the illumination rapidly. In the histogram equalization process, the histogram obtained from near-edge region is used for the histogram equalization. In the experiments, high-resolution images taken by digital camcorder are used for verifying the performance of the proposed method.

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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Comparison of Visualization Enhancement Techniques for Himawari-8 / AHI-based True Color Image Production (Himawari-8/AHI 기반 True color 영상 생산을 위한 시각화 향상 기법 비교 연구)

  • Han, Hyeon-Gyeong;Lee, Kyeong-Sang;Choi, Sungwon;Seo, Minji;Jin, Donghyun;Seong, Noh-hun;Jung, Daeseong;Kim, Honghee;Han, Kyung-Soo
    • Korean Journal of Remote Sensing
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    • v.35 no.3
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    • pp.483-489
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    • 2019
  • True color images display colors similar to natural colors. This has the advantage that it is possible to monitor rapidly the complex earth atmosphere phenomenon and the change of the surface type. Currently, various organizations are producing true color images. In Korea, it is necessary to produce true color images by replacing generations with next generation weather satellites. Therefore, in this study, visual enhancement for true color image production was performed using Top of Atmosphere (TOA) data of Advanced Himawari Imager (AHI) sensor mounted on Himawari-8 satellite. In order to improve the visualization, we performed two methods of Nonlinear enhancement and Histogram equalization. As a result, Histogram equalization showed a strong bluish image in the region over $70^{\circ}$ Solar Zenith Angle (SZA) compared to the Nonlinear enhancement and nonlinear enhancement technique showed a reddish vegetation area.

Image Contrast Enhancement Based on a Multi-Cue Histogram

  • Lee, Sung-Ho;Zhang, Dongni;Ko, Sung-Jea
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.5
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    • pp.349-353
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    • 2015
  • The conventional intensity histogram does not indicate edge information, which is important in the perception of image contrast. In this paper, we propose a multi-cue histogram (MCH) to represent a collaborative distribution of both the intensity and the edges of an image. Based on the MCH, if the intensity values have high frequency and a large gradient magnitude, they are spread into a larger dynamic range. Otherwise, the intensity values are not strongly stretched. As a result, image details, such as edges and textures, can be enhanced while artifacts and noise can be prevented, as demonstrated in the experimental results.

STD Defect Detection Algorithm by Using Cumulative Histogram in TFT-LCD Image (TFT-LCD 영상에서 누적히스토그램을 이용한 STD 결함검출 알고리즘)

  • Lee, SeungMin;Park, Kil-Houm
    • Journal of Korea Multimedia Society
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    • v.19 no.8
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    • pp.1288-1296
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    • 2016
  • The reliable detection of the limited defect in TFT-LCD images is difficult due to the small intensity difference with the background. However, the proposed detection method reliably detects the limited defect by enhancing the TFT-LCD image based on the cumulative histogram and then detecting the defect through the mean and standard deviation of the enhanced image. Notably, an image enhancement using a cumulative histogram increases the intensity contrast between the background and the limited defect, which then allows defects to be detected by using the mean and standard deviation of the enhanced image. Furthermore, through the comparison with the histogram equalization, we confirm that the proposed algorithm suppresses the emphasis of the noise. Experimental comparative results using real TFT-LCD images and pseudo images show that the proposed method detects the limited defect more reliably than conventional methods.

Bi-Histogram Equalization based on Differential Compression Method for Preserving the Trend of Natural Mean Brightness (자연스러운 영상의 평균 밝기 유지를 위한 차별적 압축 방법 기반의 분할 히스토그램 평활화)

  • Lee, Jae-Won;Hong, Sung-Hoon
    • Journal of Broadcast Engineering
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    • v.19 no.4
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    • pp.453-467
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    • 2014
  • A typical histogram equalization contrast enhancement effect for improving the image quality is excellent. However, because it appears that excessive changes of the brightness values, The average brightness of the image is changing in units of frames of applications such as a TV video is unsuitable. In order to solve these drawbacks, a modified method of histogram equalization on various studies have been made. But the result images of existing methods sometimes shown visual degradations such as over-enhancement and false contouring. In this paper, we propose improved contrast enhancement method through bi-histogram equalization using target mean brightness based on differential compression method. The proposed method is based on the average brightness value by dividing the histogram, the histogram for each zone, according to the frequency differential of compression. And equalize the modified histogram based on target mean brightness. This allows to suppress deterioration of picture quality, and changes in the average brightness of each frame of video, while maintaining and improving the contrast. Experimental results show that the proposed method compared to the conventional method, the average brightness of each frame from a movie well maintained, and no degradation of the image quality showed a good effect to improve the contrast.

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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Image Quality Enhancement by Using Logistic Equalization Function (로지스틱 평활화 함수에 의한 영상의 화질개선)

  • Cho, Yong-Hyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.1
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    • pp.30-35
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    • 2010
  • This paper presents a quality enhancement of images by using a histogram equalization based on the symmetric logistic function. 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 sigmoidal nonlinear transformation function, is applied to non-linearly enhance the brightness of the image according to its intensity level frequency. We propose a flexible and symmetrical logistic function by only using the intensity with maximum frequency in an histogram and the total number of pixels. The proposed function decreases the computation load of an exponential function in the traditional logistic function. The proposed method has been applied for equalizing 5 images with a different resolution and histogram distribution. The experimental results show that the proposed method has the superior enhancement performances compared with the source images and the traditional global histogram equalization, respectively.

FPGA-based Implementation of Fast Histogram Equalization for Image Enhancement (영상 품질 개선을 위한 FPGA 기반 고속 히스토그램 평활화 회로 구현)

  • Ryu, Sang-Moon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.11
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    • pp.1377-1383
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    • 2019
  • Histogram equalization is the most frequently used algorithm for image enhancement. Its hardware implementation significantly outperforms in time its software version. The overall performance of FPGA-based implementation of histogram equalization can be improved by applying pipelining in the design and by exploiting the multipliers and a lot of SRAM blocks which are embedded in recent FPGAs. This work proposes how to implement a fast histogram equalization circuit for 8-bit gray level images. The proposed design contains a FIFO to perform equalization on an image while the histogram for next image is being calculated. Because of some overlap in time for histogram equalization, embedded multipliers and pipelined design, the proposed design can perform histogram equalization on a pixel nearly at a clock. And its dual parallel version outperforms in time almost two times over the original one.

Speech Recognition through Speech Enhancement (음질 개선을 통한 음성의 인식)

  • Cho, Jun-Hee;Lee, Kee-Seong
    • Proceedings of the KIEE Conference
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    • 2003.11c
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    • pp.511-514
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    • 2003
  • The human being uses speech signals to exchange information. When background noise is present, speech recognizers experience performance degradations. Speech recognition through speech enhancement in the noisy environment was studied. Histogram method as a reliable noise estimation approach for spectral subtraction was introduced using MFCC method. The experiment results show the effectiveness of the proposed algorithm.

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