|
Web
Education
A performance comparison among different super-resolution ...
bib0165 Ji H, Fermüller C. Wavelet-based super-resolution reconstruction: theory and algorithm. In: ECCV; 2006. p. 295-307. Google Scholar Digital Library; bib0170 H. Ji, C. Fermuller, Robust wavelet-based super-resolution reconstruction: theory and algorithm, IEEE Trans Pattern Anal Mach Intell, 31 (2009) 649-660. Google Scholar Digital Library...
Facial image super-resolution guided by adaptive geometric ...
This paper addresses the traditional issue of restoring a high-resolution (HR) facial image from a low-resolution (LR) counterpart. Current state-of-the-art super-resolution (SR) methods commonly adopt the convolutional neural networks to learn a non-linear complex mapping between paired LR and HR images. They discriminate local patterns expressed by the neighboring pixels along the planar ......
A deep convolutional neural network using directional ...
For the last few years, researchers have had great successes from deep networks in many low‐level computer vision applications, such as denoising 21-23 and super‐resolution applications. 24, 25 Inspired by the success of the deep convolutional neural network, we propose a novel low‐dose CT denoising framework designed to detect and remove ......
GitHub - zziz/pwc: Papers with code. Sorted by stars ...
Papers with code. Sorted by stars. Updated weekly. - zziz/pwc
Multi-penalty conditional random field approach to super ...
The majority of these methods focus on image enhancement based on a single data acquisition, which include: (i) de-convolution methods [15, 16] that aim to reduce the effect of OCT PSF on the spatial resolution of acquired OCT image; (ii) different sampling methods in the K-space for the reconstruction of OCT images with higher spatial ...
Super-Resolution Reconstruction Algorithm To MODIS Remote ...
Therefore, super-resolution (SR) image reconstruction techniques, which can reconstruct one or a set of HR images from a sequence of low-resolution (LR) images of the same scene, have widely been researched in the last two decades. Multi-frame SR problem was first formulated by Tsai and Huang in the frequency domain. They proposed a formulation ......
A Total Variation Regularization Based Super-Resolution ...
Super-resolution (SR) reconstruction technique is capable of producing a high-resolution image from a sequence of low-resolution images. In this paper, we study an efficient SR algorithm for digital video. To effectively deal with the intractable problems in SR video reconstruction, such as inevitable motion estimation errors, noise, blurring, missing regions, and compression artifacts, the ......
|
