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Deep Neural Network for Image Super Resolution Driven by Prior Denoising
Nantong Daxue xuebao. Ziran kexue ban, 2021 In order to improve image super resolution, a double layer convolution neural network in image denoising is embedded in image restoration tasks. The image super resolution method driven by prior denoising with deep neural network is proposed.
CHENG Fanqiang;ZHU Yonggui;, ZHU Yonggui
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Efficient Long-Range Attention Network for Image Super-resolution [PDF]
European Conference on Computer Vision, 2022 Recently, transformer-based methods have demonstrated impressive results in various vision tasks, including image super-resolution (SR), by exploiting the self-attention (SA) for feature extraction.
Xindong Zhang +3 more
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IET Image Processing, 2023 In recent years, terahertz imaging technology has been widely used in security, medicine, and other fields. However, the image resolution is low due to the limits of imaging equipment and diffraction. Traditional super‐resolution methods based on machine
Huanyu Liu, Haipeng Guo, Xiaodong Liu
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A Review of GAN-Based Super-Resolution Reconstruction for Optical Remote Sensing Images
Remote Sensing, 2023 High-resolution images have a wide range of applications in image compression, remote sensing, medical imaging, public safety, and other fields. The primary objective of super-resolution reconstruction of images is to reconstruct a given low-resolution ...
Xuan Wang +3 more
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Deeply-Recursive Convolutional Network for Image Super-Resolution [PDF]
Computer Vision and Pattern Recognition, 2015 We propose an image super-resolution method (SR) using a deeply-recursive convolutional network (DRCN). Our network has a very deep recursive layer (up to 16 recursions).
Jiwon Kim, Jung Kwon Lee, Kyoung Mu Lee
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Super-Resolution Imaging [PDF]
, 2019 This chapter examines multiframe image super-resolution in a probabilistic framework. Many multiframe super-resolution algorithms begin by a point estimate of the unknown latent parameters, such as those describing the motion or the blur function. The focus of this chapter is on alternatives to this practice that can yield superior super-resolution ...
Pickup, L +3 more
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Ultrasound Image Enhancement using Super Resolution
Biomedical Engineering Advances, 2022 Within today's day and age, amongst women who fall under the bracket of being of reproductive age, when discussion about Gynecologic tumors comes forward, Uterine Fibroids are found to be abundant.
Ashwini Sawant, Sujata Kulkarni
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TnTViT-G: Transformer in Transformer Network for Guidance Super Resolution
IEEE Access, 2023 Image Super Resolution is a potential approach that can improve the image quality of low-resolution optical sensors, leading to improved performance in various industrial applications.
Armin Mehri +2 more
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Super-resolution in computational imaging [PDF]
Micron, 2003 Super-resolution is a word used in different contexts but mainly in the case of methods aimed at improving the resolution of an optical instrument beyond the diffraction limit. Such a result may be achieved by means of specific instrumental techniques (such as, for instance, interferometry) or by means of a suitable processing of a digital image; in ...
BERTERO, MARIO, BOCCACCI, PATRIZIA
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NAFSSR: Stereo Image Super-Resolution Using NAFNet [PDF]
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022 Stereo image super-resolution aims at enhancing the quality of super-resolution results by utilizing the complementary information provided by binocular systems.
Xiaojie Chu, Liangyu Chen, Wenqing Yu
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