Advances in Image Enhancement
In the era of the Internet of Things, images have played important roles in human–computer interactions, and with the arrival of big data technology, people have higher requirements regarding image quality, especially for images collected in dark light. This can be addressed through the development...
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| フォーマット: | Online |
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| 言語: | 英語 |
| 出版事項: |
MDPI - Multidisciplinary Digital Publishing Institute
2023
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| 主題: | |
| オンライン･アクセス: | ONIX_20230714_9783036579412_49 |
| タグ: |
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| _version_ | 1869527997677043712 |
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| collection | Directory of Open Access Books |
| description | In the era of the Internet of Things, images have played important roles in human–computer interactions, and with the arrival of big data technology, people have higher requirements regarding image quality, especially for images collected in dark light. This can be addressed through the development of camera hardware quality, i.e., the resolution and exposure time of cameras, which may require high computational costs. As an alternative, image enhancement techniques can exact salient features to improve the quality of captured images according to the differences in diverse features, although they suffer from some challenges, i.e., a low contrast, artifacts, and overexposure, thus making it decidedly necessary to determine how to use advanced image enhancement techniques. The topic of advances in the image enhancement of electronics is presented in this reprint, which brings together the research accomplishments of researchers from academia and industry. The secondary goal of this reprint is to display the latest research results of advances in image enhancement. |
| format | Online |
| id | doab-20.500.12854ir-101350 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1013502024-03-30T12:51:29Z Advances in Image Enhancement Tian, Chunwei Ren, Wenqi Liang, Yudong dual networks enhanced CNN fine learning block image super-resolution attention mechanism convolutional neural networks deep learning generative adversarial networks multiple domains translate images restart strategy adaptive adjustment particle swarm optimization spline interpolation image denoising GAN optimization algorithm autoencoder ResNet object detection YOLOv5s image segmentation wavelet scattering loss function active contour medical image image stitching camera calibration layered projection binocular ranging stereo correction HOG feature fusion DHV recognition image enhancement cross stage partial network zero-reference Ghost module NDT registration map building RandLa-Net random sampling semantic segmentation capsule network power line scene recognition complex background Visual SLAM dynamic scene YOLOv5 K-means clustering probability update side-scan sonar segmentation CNN SE-block multi-channel blockchain technology electronic bidding system design A-star algorithm artificial potential field method least squares method path planning night image dehazing encoder–decoder architecture image fusion multi-scale network serial architecture U-net blind watermark removal low illumination Retinex theory histogram equalization wavelet transform color moments non-local mean filter thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science In the era of the Internet of Things, images have played important roles in human–computer interactions, and with the arrival of big data technology, people have higher requirements regarding image quality, especially for images collected in dark light. This can be addressed through the development of camera hardware quality, i.e., the resolution and exposure time of cameras, which may require high computational costs. As an alternative, image enhancement techniques can exact salient features to improve the quality of captured images according to the differences in diverse features, although they suffer from some challenges, i.e., a low contrast, artifacts, and overexposure, thus making it decidedly necessary to determine how to use advanced image enhancement techniques. The topic of advances in the image enhancement of electronics is presented in this reprint, which brings together the research accomplishments of researchers from academia and industry. The secondary goal of this reprint is to display the latest research results of advances in image enhancement. 2023-07-14T14:26:10Z 2023-07-14T14:26:10Z 2023 book ONIX_20230714_9783036579412_49 9783036579412 9783036579405 https://directory.doabooks.org/handle/20.500.12854/101350 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/7445 https://mdpi.com/books/pdfview/book/7445 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-7940-5 10.3390/books978-3-0365-7940-5 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036579412 9783036579405 330 Basel open access |
| spellingShingle | dual networks enhanced CNN fine learning block image super-resolution attention mechanism convolutional neural networks deep learning generative adversarial networks multiple domains translate images restart strategy adaptive adjustment particle swarm optimization spline interpolation image denoising GAN optimization algorithm autoencoder ResNet object detection YOLOv5s image segmentation wavelet scattering loss function active contour medical image image stitching camera calibration layered projection binocular ranging stereo correction HOG feature fusion DHV recognition image enhancement cross stage partial network zero-reference Ghost module NDT registration map building RandLa-Net random sampling semantic segmentation capsule network power line scene recognition complex background Visual SLAM dynamic scene YOLOv5 K-means clustering probability update side-scan sonar segmentation CNN SE-block multi-channel blockchain technology electronic bidding system design A-star algorithm artificial potential field method least squares method path planning night image dehazing encoder–decoder architecture image fusion multi-scale network serial architecture U-net blind watermark removal low illumination Retinex theory histogram equalization wavelet transform color moments non-local mean filter thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science Advances in Image Enhancement |
| title | Advances in Image Enhancement |
| title_full | Advances in Image Enhancement |
| title_fullStr | Advances in Image Enhancement |
| title_full_unstemmed | Advances in Image Enhancement |
| title_short | Advances in Image Enhancement |
| title_sort | advances in image enhancement |
| topic | dual networks enhanced CNN fine learning block image super-resolution attention mechanism convolutional neural networks deep learning generative adversarial networks multiple domains translate images restart strategy adaptive adjustment particle swarm optimization spline interpolation image denoising GAN optimization algorithm autoencoder ResNet object detection YOLOv5s image segmentation wavelet scattering loss function active contour medical image image stitching camera calibration layered projection binocular ranging stereo correction HOG feature fusion DHV recognition image enhancement cross stage partial network zero-reference Ghost module NDT registration map building RandLa-Net random sampling semantic segmentation capsule network power line scene recognition complex background Visual SLAM dynamic scene YOLOv5 K-means clustering probability update side-scan sonar segmentation CNN SE-block multi-channel blockchain technology electronic bidding system design A-star algorithm artificial potential field method least squares method path planning night image dehazing encoder–decoder architecture image fusion multi-scale network serial architecture U-net blind watermark removal low illumination Retinex theory histogram equalization wavelet transform color moments non-local mean filter thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science |
| topic_facet | dual networks enhanced CNN fine learning block image super-resolution attention mechanism convolutional neural networks deep learning generative adversarial networks multiple domains translate images restart strategy adaptive adjustment particle swarm optimization spline interpolation image denoising GAN optimization algorithm autoencoder ResNet object detection YOLOv5s image segmentation wavelet scattering loss function active contour medical image image stitching camera calibration layered projection binocular ranging stereo correction HOG feature fusion DHV recognition image enhancement cross stage partial network zero-reference Ghost module NDT registration map building RandLa-Net random sampling semantic segmentation capsule network power line scene recognition complex background Visual SLAM dynamic scene YOLOv5 K-means clustering probability update side-scan sonar segmentation CNN SE-block multi-channel blockchain technology electronic bidding system design A-star algorithm artificial potential field method least squares method path planning night image dehazing encoder–decoder architecture image fusion multi-scale network serial architecture U-net blind watermark removal low illumination Retinex theory histogram equalization wavelet transform color moments non-local mean filter thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science |
| url | ONIX_20230714_9783036579412_49 |