• Title/Summary/Keyword: Multi Scale Retinex

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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.

Enhanced Integrated Multi-scale Retinex based on CIELAB Color Space for Improving Color Reproduction (색 재현 개선을 위한 CIELAB 색 공간 기반의 향상된 Multi -scale Retinex)

  • Kyung, Wang-Jun;Lee, Tae-Hyoung;Lee, Cheol-Hee;Ha, Yeong-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.1
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    • pp.1-7
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    • 2011
  • In this paper, we propose the digital image enhancement method including local tone reproduction and preservation of the hue. In recent studies, an integrated multi-scale retinex (IMSR) has produced great naturalness in the resulting images through enhancement of visibility in dark area in input images. However, most methods, including IMSR, work in RGB color spaces. As such, this produces hue distortion from the perspective of the human visual system, that is, hue distortion in CIELAB color space. Accordingly, this paper proposes an tone reproduction and enhancement of saturation method in a device-independent color space, CIELAB, to preserve the hue and obtain a high contrast and naturalness. First, to achieve the desired objectives, the IMSR is then applied to only the $L^*$ values in CIELAB color space, normalization, and simple mapping function, thereby preserving the balance of the color components and enhancement of visibility. Then, saturation adjustment is performed by applying the ratio of the chroma variation at the sRGB gamut boundary according to the corrected luminance. In experiments, the proposed method is shown to improve the visibility in dark shadows and bright regions in the resulting images and reduce any color distortion then preference test are performed.

Color Improvement of Retinex Image Using the Maximum Color Difference Signal Table (최대 색차신호 표를 이용한 Retinex 영상의 컬러 향상)

  • Lee, Jae-Won;Jung, Jee-Hoon;Hong, Sung-Hoon
    • Journal of Broadcast Engineering
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    • v.17 no.5
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    • pp.851-863
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    • 2012
  • Retinex algorithm enhances the contrast of image through visibility improvement. However, the conventional Retinex methods may produces color distortions due to error of hue representation and over-saturation since the methods work in RGB color space. In this paper, we propose a new Retinex algorithm with color correction, which improves contrast by using MSR(Multi-Scale Retinex) working in YCbCr color space and adaptively compensates the color saturation based on the maximum color difference table. Our algorithm maps the color difference signals to the correct gamut to prevent over-saturation phenomenon by considering the correlation between luminance and hue dependent saturation. Simulations results show that the proposed method gives better color improvement compared to the conventional methods.

An image enhancement-based License plate detection method for Naturally Degraded Images

  • Khan, Khurram;Choi, Myung Ryul
    • Journal of IKEEE
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    • v.22 no.4
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    • pp.1188-1194
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    • 2018
  • This paper proposes an image enhancement-based license plate detection algorithm to improve the overall performance of system. Non-uniform illumination conditions have huge impact on overall plate detection system accuracy. In this paper, we propose an algorithm for color image enhancement-based license plate detection for improving accuracy of images degraded by excessively strong and low sunlight. Firstly, the image is enhanced by Multi-Scale Retinex algorithm. Secondly, a plate detection method is employed to take advantage of geometric properties of connected components, which can significantly reduce the undesired plate regions. Finally, intersection over union method is applied for detecting the accurate location of number plate. Experimental results show that the proposed method significantly improves the accuracy of plate detection system.

Enhancement of Faded Images Using Integrated Compensation Coefficients Based on Multi-Scale Gray World Algorithm (다중크기 회색계 알고리즘 기반의 통합된 보정 계수를 이용한 바랜 영상 개선)

  • Kyung, Wang-Jun;Kim, Dae-Chul;Ha, Yeong-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39A no.8
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    • pp.459-466
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    • 2014
  • Fading effect of old pictures and printings is shown up differently according to the ink property, temperature, humidity, illuminants, and so on. Faded image enhancement techniques based on illuminant estimation are proposed such as the gray world algorithm and white patch retinex methods. However, conventional simple operators are not suitable for enhancing faded images because partial fading effect is appeared differently. Thus, this paper presents a color enhancement algorithm based on integrating correction coefficients for faded images. First, the proposed method adopts local process by using multi-scale average mask. The coefficients for each multi-scale average mask are obtained to apply the gray world algorithm. Then, integrating the coefficients with weights is performed to calculate correction ratio for red and blue channels in the gray world assumption. Finally, the enhanced image is obtained by applying the integrated coefficients to the gray world algorithm. In the experimental results, the proposed method reproduces better colors for both wholly and partially faded images compared with the previous methods.

Multi Scale Tone Mapping Model Using Visual Brightness Functions for HDR Image Compression (HDR 영상 압축을 위한 시각 밝기 함수를 이용한 다중 스케일 톤 맵핑 모델)

  • Kwon, Hyuk-Ju;Lee, Sung-Hak;Chae, Seok-Min;Sohng, Kyu-Ik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37A no.12
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    • pp.1054-1064
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    • 2012
  • HDR (high dynamic range) tone mapping algorithms are used in image processing that reduces the dynamic range of an image to be displayed on LDR (low dynamic range) devices properly. The retinex is one of the tone mapping algorithms to provide dynamic range compression, color constancy, and color rendition. It has been developed through multi-scale methods and luminance-based methods. Retinex algorithms still have drawbacks such as the emphasized noise and desaturation. In this paper, we propose a multi scale tone mapping algorithm for enhancement of contrast, saturation, and noise of HDR rendered images based on visual brightness functions. In the proposed algorithm, HSV color space has been used for preserving the hue and saturation of images. And the algorithm includes the estimation of minimum and maximum luminance level and a visual gamma function for the variation of viewing conditions. And subjective and objective evaluations show that proposed algorithm is better than existing algorithms. The proposed algorithm is expected to image quality enhancement in some fields that require a improvement of the dynamic range due to the changes in the viewing condition.

Color Enhancement in Images with Single CCD camera in Night Vision Environment

  • Hwang, Wonjun;Ko, Hanseok
    • Proceedings of the IEEK Conference
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    • 2000.07a
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    • pp.58-61
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    • 2000
  • In this paper, we describe an effective method to enhance the color night images with spatio-temporal multi-scale retinex focused to the Intelligent Transportation System (ITS) applications such as in the single CCD based Electronic Toll Collection System (ETCS). The basic spatial retinex is known to provide color constancy while effectively removing local shades. However, it is relatively ineffective in night vision enhancement. Our proposed method, STMSR, exploits the iterative time averaging of image sequences to suppress the noise in consideration of the moving vehicles in image frame. In the STMSR method, the spatial term makes the dark images distinguishable and preserves the color information day and night while the temporal term reduces the noise effect for sharper and clearer reconstruction of the contents in each image frame. We show through representative simulations that incorporating both terms in the modeling produces the output sequential images visually more pleasing than the original dim images.

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Face Detection Based On Multi-Scale Retinex (멀티 스케일 레티넥스 기반의 얼굴 인식)

  • Park, Sung-Hyun;Lee, June-Hwan;Rhee, Sang-Burm
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.733-734
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    • 2006
  • The Face Area Detection has an extensive error range of abstraction probabilities by image illuminations and background conditions. In this paper, to reduce error ranges of abstraction probabilities by factors such as illuminations and backgrounds, we made use of Retinex and the Face Area Detection algorithm together. In comparison with other previous methods[4], our proposed algorithm showed stabler and elevated detection rate.

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A Comparative Study on Image Enhancement Methods for Low Contrast Images (저대비 영상을 위한 영상향상 기법들의 비교연구)

  • Kim Yong-Soo;Kim Nam-Jin;Lee Se-Yul
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2005.04a
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    • pp.269-272
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    • 2005
  • The principal objective of enhancement methods is to process an image so that the result is more suitable than the original image for a specific application. Images taken in the night can be low-contrast images because of poor environments. In this paper, we compare the structure of ICECA(Image Contrast Enhancement technique using Clustering Algorithm) with the structures of HE(Histogram Equalization), BBHE(Brightness preserving Bi-Histogram Equalization), and Multi -Scale Retinex(MSR). We compared performances of image enhancement methods by applying these methods to a set of diverse images.

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Adaptive Enhancement Method for Robot Sequence Motion Images

  • Yu Zhang;Guan Yang
    • Journal of Information Processing Systems
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    • v.19 no.3
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    • pp.370-376
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    • 2023
  • Aiming at the problems of low image enhancement accuracy, long enhancement time and poor image quality in the traditional robot sequence motion image enhancement methods, an adaptive enhancement method for robot sequence motion image is proposed. The feature representation of the image was obtained by Karhunen-Loeve (K-L) transformation, and the nonlinear relationship between the robot joint angle and the image feature was established. The trajectory planning was carried out in the robot joint space to generate the robot sequence motion image, and an adaptive homomorphic filter was constructed to process the noise of the robot sequence motion image. According to the noise processing results, the brightness of robot sequence motion image was enhanced by using the multi-scale Retinex algorithm. The simulation results showed that the proposed method had higher accuracy and consumed shorter time for enhancement of robot sequence motion images. The simulation results showed that the image enhancement accuracy of the proposed method could reach 100%. The proposed method has important research significance and economic value in intelligent monitoring, automatic driving, and military fields.