基于智能手机摄影的人耳图像暗通道增强研究

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Dongxin Lu, Danni Zheng, Lei Kou, Qingfeng Li, Wende Ke
{"title":"基于智能手机摄影的人耳图像暗通道增强研究","authors":"Dongxin Lu,&nbsp;Danni Zheng,&nbsp;Lei Kou,&nbsp;Qingfeng Li,&nbsp;Wende Ke","doi":"10.1002/cpe.8216","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>The experienced doctors can alleviate symptoms such as headaches, insomnia, anxiety, and depression by observing the patient's ears and massaging specific areas. In order to achieve remote ear condition diagnosis and guide patients to massage their ears independently through the network, patients can use their mobile phones to take and send photos of ears to doctors. However, due to significant differences in the clarity of photos taken by different mobile phones, as well as susceptibility to haze, lighting, jitter, and low pixels, the quality of photos is poor, which affects the accuracy of remote diagnosis by doctors. This study adopted an image preprocessing method based on He Kaiming's dark channel prior dehazing method to enhance the original ear images captured by mobile phones. The dehazing algorithm was used to remove the haze effect of the ear images, improving image quality and contrast, making the wrinkles, protrusions, pigmentation and other areas of the ear more obvious. The experiment has showed the comparison by adjusting weight from 15% to 95% between two methods—dark channel prior method and the dark channel prior method after preprocessing, which has proven the effectiveness of dehazing method in human ear images taken by mobile phones. The image quality after preprocessing and dehazing is widely recognized and accepted by doctors at hospitals in Hangzhou, China.</p>\n </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"36 22","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dark channel enhancement research on human ear images based on smartphone photography\",\"authors\":\"Dongxin Lu,&nbsp;Danni Zheng,&nbsp;Lei Kou,&nbsp;Qingfeng Li,&nbsp;Wende Ke\",\"doi\":\"10.1002/cpe.8216\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>The experienced doctors can alleviate symptoms such as headaches, insomnia, anxiety, and depression by observing the patient's ears and massaging specific areas. In order to achieve remote ear condition diagnosis and guide patients to massage their ears independently through the network, patients can use their mobile phones to take and send photos of ears to doctors. However, due to significant differences in the clarity of photos taken by different mobile phones, as well as susceptibility to haze, lighting, jitter, and low pixels, the quality of photos is poor, which affects the accuracy of remote diagnosis by doctors. This study adopted an image preprocessing method based on He Kaiming's dark channel prior dehazing method to enhance the original ear images captured by mobile phones. The dehazing algorithm was used to remove the haze effect of the ear images, improving image quality and contrast, making the wrinkles, protrusions, pigmentation and other areas of the ear more obvious. The experiment has showed the comparison by adjusting weight from 15% to 95% between two methods—dark channel prior method and the dark channel prior method after preprocessing, which has proven the effectiveness of dehazing method in human ear images taken by mobile phones. The image quality after preprocessing and dehazing is widely recognized and accepted by doctors at hospitals in Hangzhou, China.</p>\\n </div>\",\"PeriodicalId\":55214,\"journal\":{\"name\":\"Concurrency and Computation-Practice & Experience\",\"volume\":\"36 22\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Concurrency and Computation-Practice & Experience\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cpe.8216\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Concurrency and Computation-Practice & Experience","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cpe.8216","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0

摘要

摘要经验丰富的医生可以通过观察患者的耳朵并按摩特定部位来缓解头痛、失眠、焦虑和抑郁等症状。为了实现远程耳部病情诊断,并通过网络指导患者自主按摩耳朵,患者可以使用手机拍摄耳朵的照片并发送给医生。然而,由于不同手机拍摄的照片清晰度差异较大,且易受雾霾、光线、抖动、像素低等因素影响,照片质量较差,影响了医生远程诊断的准确性。本研究采用基于何开明的暗通道先验去斑方法的图像预处理方法,对手机拍摄的原始耳部图像进行增强处理。通过去毛刺算法去除耳部图像的雾度效应,提高图像质量和对比度,使耳部的皱纹、突起、色素沉着等区域更加明显。实验显示,通过将权重从 15% 调整到 95%,两种方法--暗通道先验法和预处理后的暗通道先验法--进行了对比,证明了去噪方法在手机拍摄的人耳图像中的有效性。预处理和去毛刺后的图像质量得到了中国杭州医院医生的广泛认可和接受。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dark channel enhancement research on human ear images based on smartphone photography

The experienced doctors can alleviate symptoms such as headaches, insomnia, anxiety, and depression by observing the patient's ears and massaging specific areas. In order to achieve remote ear condition diagnosis and guide patients to massage their ears independently through the network, patients can use their mobile phones to take and send photos of ears to doctors. However, due to significant differences in the clarity of photos taken by different mobile phones, as well as susceptibility to haze, lighting, jitter, and low pixels, the quality of photos is poor, which affects the accuracy of remote diagnosis by doctors. This study adopted an image preprocessing method based on He Kaiming's dark channel prior dehazing method to enhance the original ear images captured by mobile phones. The dehazing algorithm was used to remove the haze effect of the ear images, improving image quality and contrast, making the wrinkles, protrusions, pigmentation and other areas of the ear more obvious. The experiment has showed the comparison by adjusting weight from 15% to 95% between two methods—dark channel prior method and the dark channel prior method after preprocessing, which has proven the effectiveness of dehazing method in human ear images taken by mobile phones. The image quality after preprocessing and dehazing is widely recognized and accepted by doctors at hospitals in Hangzhou, China.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Concurrency and Computation-Practice & Experience
Concurrency and Computation-Practice & Experience 工程技术-计算机:理论方法
CiteScore
5.00
自引率
10.00%
发文量
664
审稿时长
9.6 months
期刊介绍: Concurrency and Computation: Practice and Experience (CCPE) publishes high-quality, original research papers, and authoritative research review papers, in the overlapping fields of: Parallel and distributed computing; High-performance computing; Computational and data science; Artificial intelligence and machine learning; Big data applications, algorithms, and systems; Network science; Ontologies and semantics; Security and privacy; Cloud/edge/fog computing; Green computing; and Quantum computing.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信