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...
Format: | eBook |
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Language: | English |
Published: |
Basel
MDPI - Multidisciplinary Digital Publishing Institute
2023
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Subjects: | |
Online Access: | Open Access: DOAB: description of the publication Open Access: DOAB, download the publication |
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020 | |a 9783036579412 | ||
020 | |a books978-3-0365-7940-5 | ||
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041 | 0 | |a eng | |
042 | |a dc | ||
072 | 7 | |a KNTX |2 bicssc | |
072 | 7 | |a UY |2 bicssc | |
720 | 1 | |a Tian, Chunwei |4 edt | |
720 | 1 | |a Liang, Yudong |4 edt | |
720 | 1 | |a Liang, Yudong |4 oth | |
720 | 1 | |a Ren, Wenqi |4 edt | |
720 | 1 | |a Ren, Wenqi |4 oth | |
720 | 1 | |a Tian, Chunwei |4 oth | |
245 | 0 | 0 | |a Advances in Image Enhancement |
260 | |a Basel |b MDPI - Multidisciplinary Digital Publishing Institute |c 2023 | ||
300 | |a 1 online resource (330 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
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506 | 0 | |a Open Access |f Unrestricted online access |2 star | |
520 | |a 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. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |u https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Computer science |2 bicssc | |
650 | 7 | |a Information technology industries |2 bicssc | |
653 | |a A-star algorithm | ||
653 | |a active contour | ||
653 | |a adaptive adjustment | ||
653 | |a artificial potential field method | ||
653 | |a attention mechanism | ||
653 | |a autoencoder | ||
653 | |a binocular ranging | ||
653 | |a blind watermark removal | ||
653 | |a blockchain technology | ||
653 | |a camera calibration | ||
653 | |a capsule network | ||
653 | |a CNN | ||
653 | |a color moments | ||
653 | |a complex background | ||
653 | |a convolutional neural networks | ||
653 | |a cross stage partial network | ||
653 | |a deep learning | ||
653 | |a DHV recognition | ||
653 | |a dual networks | ||
653 | |a dynamic scene | ||
653 | |a electronic bidding | ||
653 | |a encoder-decoder architecture | ||
653 | |a enhanced CNN | ||
653 | |a feature fusion | ||
653 | |a fine learning block | ||
653 | |a GAN | ||
653 | |a generative adversarial networks | ||
653 | |a Ghost module | ||
653 | |a histogram equalization | ||
653 | |a HOG | ||
653 | |a image denoising | ||
653 | |a image enhancement | ||
653 | |a image fusion | ||
653 | |a image segmentation | ||
653 | |a image stitching | ||
653 | |a image super-resolution | ||
653 | |a K-means clustering | ||
653 | |a layered projection | ||
653 | |a least squares method | ||
653 | |a loss function | ||
653 | |a low illumination | ||
653 | |a map building | ||
653 | |a medical image | ||
653 | |a multi-channel | ||
653 | |a multi-scale network | ||
653 | |a multiple domains | ||
653 | |a NDT registration | ||
653 | |a night image dehazing | ||
653 | |a non-local mean filter | ||
653 | |a object detection | ||
653 | |a optimization algorithm | ||
653 | |a particle swarm optimization | ||
653 | |a path planning | ||
653 | |a power line scene recognition | ||
653 | |a probability update | ||
653 | |a RandLa-Net | ||
653 | |a random sampling | ||
653 | |a ResNet | ||
653 | |a restart strategy | ||
653 | |a Retinex theory | ||
653 | |a SE-block | ||
653 | |a segmentation | ||
653 | |a semantic segmentation | ||
653 | |a serial architecture | ||
653 | |a side-scan sonar | ||
653 | |a spline interpolation | ||
653 | |a stereo correction | ||
653 | |a system design | ||
653 | |a translate images | ||
653 | |a U-net | ||
653 | |a Visual SLAM | ||
653 | |a wavelet scattering | ||
653 | |a wavelet transform | ||
653 | |a YOLOv5 | ||
653 | |a YOLOv5s | ||
653 | |a zero-reference | ||
793 | 0 | |a DOAB Library. | |
856 | 4 | 0 | |u https://directory.doabooks.org/handle/20.500.12854/101350 |7 0 |z Open Access: DOAB: description of the publication |
856 | 4 | 0 | |u https://mdpi.com/books/pdfview/book/7445 |7 0 |z Open Access: DOAB, download the publication |