首页 > 最新文献

The Imaging Science Journal最新文献

英文 中文
Denoising multispectral images using non-local rank tensor decomposition and bilateral filtering based on sunflower optimization 基于向日葵优化的非局部秩张量分解和双边滤波技术对多光谱图像去噪
Pub Date : 2024-04-25 DOI: 10.1080/13682199.2024.2344900
Madhuvan Dixit, Mahesh Pawar
Image denoising is an important pre-processing process in the fields of computer vision and image processing. Traditional denoising techniques blur edges excessively and degrade image quality by re...
图像去噪是计算机视觉和图像处理领域的一个重要预处理过程。传统的去噪技术会使边缘过度模糊,降低图像质量。
{"title":"Denoising multispectral images using non-local rank tensor decomposition and bilateral filtering based on sunflower optimization","authors":"Madhuvan Dixit, Mahesh Pawar","doi":"10.1080/13682199.2024.2344900","DOIUrl":"https://doi.org/10.1080/13682199.2024.2344900","url":null,"abstract":"Image denoising is an important pre-processing process in the fields of computer vision and image processing. Traditional denoising techniques blur edges excessively and degrade image quality by re...","PeriodicalId":22456,"journal":{"name":"The Imaging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140811893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Optimized multi-scale framework for image enhancement using spatial information-based histogram equalization 利用基于空间信息的直方图均衡化优化多尺度图像增强框架
Pub Date : 2024-04-25 DOI: 10.1080/13682199.2024.2343979
D. Vijayalakshmi, Poonguzhali Elangovan, T. Sandhya Kumari, Malaya Kumar Nath
{"title":"Optimized multi-scale framework for image enhancement using spatial information-based histogram equalization","authors":"D. Vijayalakshmi, Poonguzhali Elangovan, T. Sandhya Kumari, Malaya Kumar Nath","doi":"10.1080/13682199.2024.2343979","DOIUrl":"https://doi.org/10.1080/13682199.2024.2343979","url":null,"abstract":"","PeriodicalId":22456,"journal":{"name":"The Imaging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140653940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Convolution technique for focusing of ISAR images 用于聚焦 ISAR 图像的卷积技术
Pub Date : 2024-04-10 DOI: 10.1080/13682199.2024.2340139
Palguna Kumar Reddy Gopireddy, Arun Kumar Gande, Gopi Ram, Farukh Hashmi Mohammad
Defocusing is an undesirable phenomenon in remote sensing. Defocusing arises due to the platform motion irregularity or the target motion. The focusing techniques in the literature either need the ...
散焦是遥感中的一种不良现象。散焦是由于平台运动不规则或目标运动造成的。文献中的对焦技术要么需要对焦,要么需要对焦。
{"title":"Convolution technique for focusing of ISAR images","authors":"Palguna Kumar Reddy Gopireddy, Arun Kumar Gande, Gopi Ram, Farukh Hashmi Mohammad","doi":"10.1080/13682199.2024.2340139","DOIUrl":"https://doi.org/10.1080/13682199.2024.2340139","url":null,"abstract":"Defocusing is an undesirable phenomenon in remote sensing. Defocusing arises due to the platform motion irregularity or the target motion. The focusing techniques in the literature either need the ...","PeriodicalId":22456,"journal":{"name":"The Imaging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140575192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Segnet with Unet3+ and EfficientNet: a novel framework of brain tumour segmentation and classification model by multiscale attention-based deep learning techniques with hybrid heuristic improvement using 3D MRI brain images 带有 Unet3+ 和 EfficientNet 的 Segnet:利用三维核磁共振成像脑图像,通过基于多尺度注意力的深度学习技术和混合启发式改进,建立脑肿瘤分割和分类模型的新型框架
Pub Date : 2024-04-06 DOI: 10.1080/13682199.2023.2283678
Ramya D, Lakshmi C
An adaptive deep learning is recommended to segment and classify the brain tumor using 3D MRI images. Initially, the original 3D MRI images are gathered and fed into pre-processing, which is accomp...
建议采用自适应深度学习方法,利用三维核磁共振成像图像对脑肿瘤进行分割和分类。首先,收集原始的三维核磁共振成像图像并将其输入预处理,预处理完成后,对图像进行...
{"title":"Segnet with Unet3+ and EfficientNet: a novel framework of brain tumour segmentation and classification model by multiscale attention-based deep learning techniques with hybrid heuristic improvement using 3D MRI brain images","authors":"Ramya D, Lakshmi C","doi":"10.1080/13682199.2023.2283678","DOIUrl":"https://doi.org/10.1080/13682199.2023.2283678","url":null,"abstract":"An adaptive deep learning is recommended to segment and classify the brain tumor using 3D MRI images. Initially, the original 3D MRI images are gathered and fed into pre-processing, which is accomp...","PeriodicalId":22456,"journal":{"name":"The Imaging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140575275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A new degradation model and an improved SRGAN for multi-image super-resolution reconstruction 用于多图像超分辨率重建的新退化模型和改进型 SRGAN
Pub Date : 2024-03-25 DOI: 10.1080/13682199.2024.2331813
Hongan Li, Lizhi Cheng, Jun Liu
In order to solve the problems existing in multi-image super-resolution reconstruction methods, such as the difficulty of acquiring and processing multiple low-resolution images, the inability to m...
为了解决多幅图像超分辨率重建方法中存在的问题,如获取和处理多幅低分辨率图像的困难,以及无法对多幅低分辨率图像进行超分辨率重建等。
{"title":"A new degradation model and an improved SRGAN for multi-image super-resolution reconstruction","authors":"Hongan Li, Lizhi Cheng, Jun Liu","doi":"10.1080/13682199.2024.2331813","DOIUrl":"https://doi.org/10.1080/13682199.2024.2331813","url":null,"abstract":"In order to solve the problems existing in multi-image super-resolution reconstruction methods, such as the difficulty of acquiring and processing multiple low-resolution images, the inability to m...","PeriodicalId":22456,"journal":{"name":"The Imaging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140297465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Joint first and second order total variation decomposition for remote sensing images destriping 用于遥感图像去条纹的一阶和二阶总变异联合分解
Pub Date : 2024-02-22 DOI: 10.1080/13682199.2024.2320491
Ayoub Boutemedjet, Sid Ahmed Hamadouche, Nabil Belghachem
Stripe noise remains a significant source of errors and image quality degradation in remote sensing systems. A prominent approach for tackling this problem is the first-order Total Variation (TV) r...
条纹噪声仍然是遥感系统中误差和图像质量下降的一个重要来源。解决这一问题的一个突出方法是一阶总变异(TV)r...
{"title":"Joint first and second order total variation decomposition for remote sensing images destriping","authors":"Ayoub Boutemedjet, Sid Ahmed Hamadouche, Nabil Belghachem","doi":"10.1080/13682199.2024.2320491","DOIUrl":"https://doi.org/10.1080/13682199.2024.2320491","url":null,"abstract":"Stripe noise remains a significant source of errors and image quality degradation in remote sensing systems. A prominent approach for tackling this problem is the first-order Total Variation (TV) r...","PeriodicalId":22456,"journal":{"name":"The Imaging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139950860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A novel method for video enhancement under low light using BFR-SEQT technique 利用 BFR-SEQT 技术实现弱光下视频增强的新方法
Pub Date : 2024-02-13 DOI: 10.1080/13682199.2024.2315855
J. Bright Jose, R. P. Anto Kumar
As typical frame rates allow limited exposure time, camera-captured videos under low-light conditions often suffer from poor contrast and noise. Existing models failed to consider dark and light ar...
由于典型的帧速率允许的曝光时间有限,低光照条件下相机捕获的视频往往对比度差、噪点多。现有的模型没有考虑到暗光和亮光环境。
{"title":"A novel method for video enhancement under low light using BFR-SEQT technique","authors":"J. Bright Jose, R. P. Anto Kumar","doi":"10.1080/13682199.2024.2315855","DOIUrl":"https://doi.org/10.1080/13682199.2024.2315855","url":null,"abstract":"As typical frame rates allow limited exposure time, camera-captured videos under low-light conditions often suffer from poor contrast and noise. Existing models failed to consider dark and light ar...","PeriodicalId":22456,"journal":{"name":"The Imaging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139752321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Face photo-line drawings synthesis based on local extraction preserving generative adversarial networks 基于局部提取保存生成对抗网络的人脸照片线图合成
Pub Date : 2024-02-11 DOI: 10.1080/13682199.2024.2315848
Yi Lihamu·Ya Ermaimaiti, Po Wang, Ying Tezhaer· Ai Shanjiang
Facial photo-to-sketch synthesis is crucial for entertainment and criminal investigations, yet challenges persist, including local detail blurring and identity feature loss. To mitigate these probl...
从面部照片到草图的合成对于娱乐和犯罪调查至关重要,但挑战依然存在,包括局部细节模糊和身份特征丢失。为了缓解这些问题,我们需要一种新的方法。
{"title":"Face photo-line drawings synthesis based on local extraction preserving generative adversarial networks","authors":"Yi Lihamu·Ya Ermaimaiti, Po Wang, Ying Tezhaer· Ai Shanjiang","doi":"10.1080/13682199.2024.2315848","DOIUrl":"https://doi.org/10.1080/13682199.2024.2315848","url":null,"abstract":"Facial photo-to-sketch synthesis is crucial for entertainment and criminal investigations, yet challenges persist, including local detail blurring and identity feature loss. To mitigate these probl...","PeriodicalId":22456,"journal":{"name":"The Imaging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139752337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fractional Pelican African Vulture Optimization-based classification of breast cancer using mammogram images 基于分数鹈鹕非洲秃鹫优化的乳腺癌分类(使用乳房 X 光图像
Pub Date : 2024-01-04 DOI: 10.1080/13682199.2023.2298111
R. Prasad, Jayashree Prasad, Nihar M. Ranjan, Amol V. Dhumane, M. Tamboli
{"title":"Fractional Pelican African Vulture Optimization-based classification of breast cancer using mammogram images","authors":"R. Prasad, Jayashree Prasad, Nihar M. Ranjan, Amol V. Dhumane, M. Tamboli","doi":"10.1080/13682199.2023.2298111","DOIUrl":"https://doi.org/10.1080/13682199.2023.2298111","url":null,"abstract":"","PeriodicalId":22456,"journal":{"name":"The Imaging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139384635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Adaptive enhancement method of irregular low-pixel architectural design image based on lightness component 基于亮度分量的不规则低像素建筑设计图像自适应增强方法
Pub Date : 2023-12-15 DOI: 10.1080/13682199.2023.2287348
Mei Qu
This study explores adaptive enhancement for irregular, low-pixel architectural design images, focusing on lightness components. Utilizing a median filter and wavelet threshold method removes image...
本研究探讨了不规则、低像素建筑设计图像的自适应增强,重点关注亮度成分。利用中值滤波器和小波阈值法去除图像中的...
{"title":"Adaptive enhancement method of irregular low-pixel architectural design image based on lightness component","authors":"Mei Qu","doi":"10.1080/13682199.2023.2287348","DOIUrl":"https://doi.org/10.1080/13682199.2023.2287348","url":null,"abstract":"This study explores adaptive enhancement for irregular, low-pixel architectural design images, focusing on lightness components. Utilizing a median filter and wavelet threshold method removes image...","PeriodicalId":22456,"journal":{"name":"The Imaging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138682564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
期刊
The Imaging Science Journal
全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
×
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
现在去查看 取消
×
提示
确定
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1