Non-uniform illumination image enhancement algorithm based on parametric fuzzy transformation

DAI Rong

Chinese

您当前的位置：

首页 >

文章列表页 >

Non-uniform illumination image enhancement algorithm based on parametric fuzzy transformation

更新时间：2026-09-04

- Non-uniform illumination image enhancement algorithm based on parametric fuzzy transformation
- Vol. 36, Issue 12, Pages: 53-57(2019)
- 作者机构：
  
  中国民用航空飞行学院, 四川广汉,618307
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2019
- 稿件说明：
移动端阅览
戴蓉. 基于参数模糊变换的非均匀照度图像增强算法[J]. 微电子学与计算机, 2019, 36(12): 53-57.

DAI Rong. Non-uniform illumination image enhancement algorithm based on parametric fuzzy transformation[J]. 2019, 36(12): 53-57.
戴蓉. 基于参数模糊变换的非均匀照度图像增强算法[J]. 微电子学与计算机, 2019, 36(12): 53-57. DOI：

DAI Rong. Non-uniform illumination image enhancement algorithm based on parametric fuzzy transformation[J]. 2019, 36(12): 53-57. DOI：

摘要

针对非均匀照度图像中对比度和清晰度低的问题

提出了一种基于参数模糊变换的图像对比度增强算法

能够极大改善图像的主观和客观品质.该算法首先将彩色图像从RGB空间转换成HSV和LUV颜色空间

其次在LUV空间上利用模糊变换平滑原始图像的亮度分布

为了增强图像的对比度和提高暗区的细节

在隶属度函数中引入一个与HSV空间值层有关的参数

然后在HSV空间值层中采用像素加权策略用来保留大量纹理信息

最后将平滑的图像与加权的图像在HSV空间上进行组合

并转换回RGB空间

得到保留有自然度的高质量增强图像.实验结果表明

所提方法能够有效增强非均匀照度图像对比度

且整体性能要优于其他算法.

Abstract

Aiming at the problem of low contrast and low definition in non-uniform illumination images

an algorithm for enhancing image contrast using parametric fuzzy transform in luminance domain was proposed. The algorithm converts the color image from RGB space to HSV color space and LUV color space firstly

and secondly applies the fuzzy transform in the luminance domain of LUV to smooth the brightness distribution of the original image. In order to enhance the contrast of the image and improve the detail of the dark region

we introduce a parameter related to the HSV spatial value layer in the membership function. Then the proposed algorithm utilizes the pixel weighting strategy in the HSV spatial value layer to preserve a large amount of texture information. Finally

both the images are combined to form the enhanced image in HSV space and transformed to RGB space

which obtained a high quality image with naturalness preservation. The experimental results show that the overall performance of the proposed method is better than other algorithms. While effectively enhancing the contrast of non-uniform illumination images

the subjective and objective quality of the image is also greatly improved.

关键词

Keywords

references

PERFILIEVA I, SINGH A P, TIWARI S P. On the relationship among F -transform, fuzzy rough set and fuzzy topology[J]. Soft Computing, 2017, 21(13): 3513-3523. DOI: 3513

GUO X, LI Y, LING H. LIME: Low-Light Image Enhancement via Illumination Map Estimation[J]. IEEE Transactions on Image Processing, 2017, 26(2): 982-993. DOI: 982

PUSHPA MAMORIA, DEEPA RAJ. Comparison of Mamdani Fuzzy Inference System for Multiple Membership Functions[J]. I.J. Image, Graphics and Signal Processing, 2016, 8(9): 26-30. DOI: 26

YUE H, YANG J, SUN X, et al. Contrast Enhancement Based on Intrinsic Image Decomposition[J]. IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society, 2017, 26(8): 3981-3994. DOI: 3981

KANSAL S, PURWAR S, TRIPATHI R K. Image contrast enhancement using unsharp masking and histogram equalization[J]. Multimedia Tools and Applications, 2018, 77(20): 26919-26938. DOI: 26919

THORNHILL C, SMIRNOVA M. Litigation and political transformation: the case of Russia[J]. Theory and society, 2018, 47(5): 559-593. DOI: 559

TSAI Y W, CHENG F C, RUAN S J. An efficient dynamic window size selection method for 2-D histogram construction in contextual and variational contrast enhancement[J]. Multimedia Tools and Applications, 2017, 76(1): 1121-1137. DOI: 1121

张红颖, 胡文博.基于Retinex灰度增强和颜色信息的时空上下文跟踪算法[J].计算机辅助设计与图形学学报, 2017, 29(12): 173-179. DOI: 173

左芝勇.一种空间自适应的Retinex变分校正模型[J].计算机应用研究, 2018, 35(5): 1582-1585. DOI: 1582

智宁, 毛善君, 李梅.基于相对梯度正则化的Retinex变分模型及其应用[J].通信学报, 2017, 38(11): 69-79. DOI: 69

LIU C, CHENG I, ZHANG Y, et al. Enhancement of low visibility aerial images using histogram truncation and an explicit Retinex representation for balancing contrast and color consistency[J]. Isprs Journal of Photogrammetry % Remote Sensing, 2017, 128: 16-26. DOI: 16

KHOURY J E, MOAN S L, THOMAS J B, et al. Color and sharpness assessment of single image dehazing[J]. Multimedia Tools % Applications, 2017, 77(8): 1-22. DOI: 1

ZHANG J, ZHOU P, ZHANG Q. Low-Light Image Enhancement Based on Iterative Multi-Scale Guided Filter Retinex[J]. Journal of Graphics, 2018, 39(1): 1-11. DOI: 1

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

A Multi-Color Space Information Fusion Algorithm for Image Enhancement

Design of ultra-low power real-time clock circuits

Microservices anomaly detection based on the correlation of monitoring metrics

A feature-oriented context understanding and slice analysis network for tuberculosis detection

A high-efficiency charge pump for ultra-low voltage boost systems

Related Author

DANG Ling-ru

ZHU Dan

TONG Xin-xin

WANG Yu-liang

Related Institution

1 Shenyang Institute of Automation Chinese Academy of Sciences

2 University of Chinese Academy of Sciences

3 Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰