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The Imaging Science Journal最新文献

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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
The Imaging Science Journal Pub Date : 2024-04-25 DOI: 10.1080/13682199.2024.2344900
Madhuvan Dixit, Mahesh Pawar
{"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":"47 1","pages":""},"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
The Imaging Science Journal 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":"4 8","pages":""},"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
The Imaging Science Journal Pub Date : 2024-04-10 DOI: 10.1080/13682199.2024.2340139
Palguna Kumar Reddy Gopireddy, Arun Kumar Gande, Gopi Ram, Farukh Hashmi Mohammad
{"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":"84 1","pages":""},"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
The Imaging Science Journal Pub Date : 2024-04-06 DOI: 10.1080/13682199.2023.2283678
Ramya D, Lakshmi C
{"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":"29 1","pages":""},"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
The Imaging Science Journal Pub Date : 2024-03-25 DOI: 10.1080/13682199.2024.2331813
Hongan Li, Lizhi Cheng, Jun Liu
{"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":"29 1","pages":""},"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
The Imaging Science Journal Pub Date : 2024-02-22 DOI: 10.1080/13682199.2024.2320491
Ayoub Boutemedjet, Sid Ahmed Hamadouche, Nabil Belghachem
{"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":"2016 1","pages":""},"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
The Imaging Science Journal Pub Date : 2024-02-13 DOI: 10.1080/13682199.2024.2315855
J. Bright Jose, R. P. Anto Kumar
{"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":"1 1","pages":""},"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
The Imaging Science Journal Pub Date : 2024-02-11 DOI: 10.1080/13682199.2024.2315848
Yi Lihamu·Ya Ermaimaiti, Po Wang, Ying Tezhaer· Ai Shanjiang
{"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":"29 1","pages":""},"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
The Imaging Science Journal 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":"58 28","pages":""},"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
The Imaging Science Journal Pub Date : 2023-12-15 DOI: 10.1080/13682199.2023.2287348
Mei Qu
{"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":"171 1","pages":""},"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
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