• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

使用选择性滤波器的直方图均衡化。

Histogram equalization using a selective filter.

作者信息

Dyke Roberto M, Hormann Kai

机构信息

Faculty of Informatics, Università della Svizzera italiana, Via Buffi 13, 6900 Lugano, Switzerland.

出版信息

Vis Comput. 2023;39(12):6221-6235. doi: 10.1007/s00371-022-02723-8. Epub 2022 Nov 29.

DOI:10.1007/s00371-022-02723-8
PMID:37969935
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10635952/
Abstract

Many popular modern image processing software packages implement a naïve form of histogram equalization. This implementation is known to produce histograms that are not truly uniform. While exact histogram equalization techniques exist, these may produce undesirable artifacts in some scenarios. In this paper we consider the link between the established continuous theory for global histogram equalization and its discrete implementation, and we formulate a novel histogram equalization technique that builds upon and considerably improves the naïve approach. We show that we can linearly interpolate the cumulative distribution of a low-bit image by approximately dequantizing its intensities using a selective box filter. This helps to distribute the intensities more evenly. The proposed algorithm is subsequently evaluated and compared with existing works in the literature. We find that the method is capable of producing an equalized histogram that has a high entropy, while distances between similar intensities are preserved. The described approach has implications on several related image processing problems, e.g., edge detection.

摘要

许多流行的现代图像处理软件包都实现了一种简单形式的直方图均衡化。已知这种实现方式会产生并非真正均匀的直方图。虽然存在精确的直方图均衡化技术，但在某些情况下这些技术可能会产生不良伪影。在本文中，我们考虑了已有的全局直方图均衡化连续理论与其离散实现之间的联系，并制定了一种新颖的直方图均衡化技术，该技术基于简单方法并对其进行了大幅改进。我们表明，通过使用选择性盒式滤波器对低比特图像的强度进行近似去量化，我们可以对其累积分布进行线性插值。这有助于更均匀地分布强度。随后对所提出的算法进行了评估，并与文献中的现有工作进行了比较。我们发现该方法能够生成具有高熵的均衡化直方图，同时保留相似强度之间的距离。所描述的方法对几个相关的图像处理问题有影响，例如边缘检测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/96ae714424bf/371_2022_2723_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/bcb5052a54ec/371_2022_2723_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/d1b3fc1006d9/371_2022_2723_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/069f56b2e197/371_2022_2723_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/1bc0243ae502/371_2022_2723_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/13631ec584b7/371_2022_2723_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/5f7d1f08fdeb/371_2022_2723_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/4e039d18d84f/371_2022_2723_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/8baf6cabe786/371_2022_2723_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/4770b59b11ac/371_2022_2723_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/0bccbc3fb209/371_2022_2723_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/96ae714424bf/371_2022_2723_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/bcb5052a54ec/371_2022_2723_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/d1b3fc1006d9/371_2022_2723_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/069f56b2e197/371_2022_2723_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/1bc0243ae502/371_2022_2723_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/13631ec584b7/371_2022_2723_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/5f7d1f08fdeb/371_2022_2723_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/4e039d18d84f/371_2022_2723_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/8baf6cabe786/371_2022_2723_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/4770b59b11ac/371_2022_2723_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/0bccbc3fb209/371_2022_2723_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/10635952/96ae714424bf/371_2022_2723_Fig11_HTML.jpg

相似文献

1
Histogram equalization using a selective filter.使用选择性滤波器的直方图均衡化。
Vis Comput. 2023;39(12):6221-6235. doi: 10.1007/s00371-022-02723-8. Epub 2022 Nov 29.
2
A novel 3-D color histogram equalization method with uniform 1-D gray scale histogram.一种新颖的三维彩色直方图均衡化方法，具有均匀的一维灰度直方图。
IEEE Trans Image Process. 2011 Feb;20(2):506-12. doi: 10.1109/TIP.2010.2068555. Epub 2010 Aug 26.
3
Multipurpose contrast enhancement on epiphyseal plates and ossification centers for bone age assessment.骺板和骨化中心的多功能对比增强在骨龄评估中的应用。
Biomed Eng Online. 2013 Apr 8;12:27. doi: 10.1186/1475-925X-12-27.
4
Image sub-division and quadruple clipped adaptive histogram equalization (ISQCAHE) for low exposure image enhancement.用于低曝光图像增强的图像细分与四重裁剪自适应直方图均衡化（ISQCAHE）
Multidimens Syst Signal Process. 2023;34(1):25-45. doi: 10.1007/s11045-022-00853-9. Epub 2022 Sep 28.
5
Local Contrast-Based Pixel Ordering for Exact Histogram Specification.基于局部对比度的像素排序以实现精确的直方图规定
J Imaging. 2022 Sep 10;8(9):247. doi: 10.3390/jimaging8090247.
6
Scintigraphic image contrast-enhancement techniques: global and local area histogram equalization.闪烁图像对比度增强技术：全局和局部区域直方图均衡化
Eur J Nucl Med. 1981;6(6):261-4. doi: 10.1007/BF00251349.
7
[Improved Algorithm of Histogram Equalization for Image Enhancement].[用于图像增强的改进直方图均衡化算法]
Zhongguo Yi Liao Qi Xie Za Zhi. 2017 May 30;41(3):175-176. doi: 10.3969/j.issn.1671-7104.2017.03.005.
8
GPU acceleration of liver enhancement for tumor segmentation.GPU 加速肝脏增强用于肿瘤分割。
Comput Methods Programs Biomed. 2020 Feb;184:105285. doi: 10.1016/j.cmpb.2019.105285. Epub 2019 Dec 17.
9
Information granules in image histogram analysis.图像直方图分析中的信息粒度。
Comput Med Imaging Graph. 2018 Apr;65:129-141. doi: 10.1016/j.compmedimag.2017.05.003. Epub 2017 May 10.
10
Adaptive clip-limit-based bi-histogram equalization algorithm for infrared image enhancement.基于自适应限幅的双直方图均衡化红外图像增强算法
Appl Opt. 2020 Oct 1;59(28):9032-9041. doi: 10.1364/AO.395848.

引用本文的文献

1
An Advanced Whale Optimization Algorithm for Grayscale Image Enhancement.一种用于灰度图像增强的改进鲸鱼优化算法。
Biomimetics (Basel). 2024 Dec 14;9(12):760. doi: 10.3390/biomimetics9120760.
2
Diabetic retinopathy detection using Bilayered Neural Network classification model with resubstitution validation.使用具有再代入验证的双层神经网络分类模型进行糖尿病视网膜病变检测。
MethodsX. 2024 Apr 6;12:102705. doi: 10.1016/j.mex.2024.102705. eCollection 2024 Jun.

本文引用的文献

1
Image Bit-Depth Enhancement via Maximum A Posteriori Estimation of AC Signal.通过交流信号的最大后验估计实现图像比特深度增强
IEEE Trans Image Process. 2016 Jun;25(6):2896-2909. doi: 10.1109/TIP.2016.2553523. Epub 2016 Apr 13.
2
Local learned dictionaries optimized to edge orientation for inverse halftoning.针对边缘方向优化的局部学习字典用于反向半调。
IEEE Trans Image Process. 2014 Jun;23(6):2542-56. doi: 10.1109/TIP.2014.2319732. Epub 2014 Apr 24.
3
A computational approach to edge detection.一种基于计算的边缘检测方法。
IEEE Trans Pattern Anal Mach Intell. 1986 Jun;8(6):679-98.
4
Multiscale probabilistic dithering for suppressing contour artifacts in digital images.用于抑制数字图像中轮廓伪影的多尺度概率抖动
IEEE Trans Image Process. 2009 Sep;18(9):1936-45. doi: 10.1109/TIP.2009.2022293. Epub 2009 May 5.
5
A fast, high-quality inverse halftoning algorithm for error diffused halftones.一种快速、高质量的误差扩散半色调反半调算法。
IEEE Trans Image Process. 2000;9(9):1583-92. doi: 10.1109/83.862639.
6
Look-up table (LUT) method for inverse halftoning.用于逆半色调处理的查找表（LUT）方法。
IEEE Trans Image Process. 2001;10(10):1566-78. doi: 10.1109/83.951541.
7
Adaptive image contrast enhancement using generalizations of histogram equalization.自适应图像对比度增强的直方图均衡化推广方法。
IEEE Trans Image Process. 2000;9(5):889-96. doi: 10.1109/83.841534.
8
Exact histogram specification.精确的直方图规定。
IEEE Trans Image Process. 2006 May;15(5):1143-52. doi: 10.1109/tip.2005.864170.