A Study on Super Resolution Image Reconstruction for Acquired Images from Naval Combat System using Generative Adversarial Networks

2018 ◽  
Vol 19 (6) ◽  
pp. 1197-1205
Author(s):  
Dongyoung Kim
Keyword(s):  
Image Reconstruction ◽  
Super Resolution ◽  
Generative Adversarial Networks ◽  
Resolution Image ◽  
Adversarial Networks

scholarly journals Super Resolution: A Simplified Approach Using GANs

2020 ◽  
Vol 5 (7) ◽  
pp. 188-191
Author(s):  
Dr. Naveena C ◽  
Thanush M ◽  
Vinay N.B ◽  
Yaser Ahmed N
Keyword(s):  
Computer Vision ◽  
Super Resolution ◽  
Generative Adversarial Networks ◽  
Digital Cameras ◽  
Simplified Approach ◽  
Resolution Image ◽  
Adversarial Networks ◽  
Current Scenario ◽  
Computer Vision Applications ◽  
The Cost

The project entitled “Super-Resolution: A simplified approach using GANs”, aims to construct a Higher Resolution image from a Lower Resolution image, without losing much detail. In other words, it is a process of up-sampling of an under-sampled image. In the current scenario, there is a high reliance on hardware improvements to capture better highresolution images. Although many digital cameras provide enough HR-imagery, the cost to construct and purchase such a high-end camera is high. Also, many computer vision applications like medical imaging, forensic and many more still have a strong demand for higher resolution imagery which is likely to be exceeded by the capabilities of these HR digital cameras we have today. To cope with this demand, a method to generate an HR image is shown using Generative Adversarial Networks (GANs).

Fast MAP-based multiframe super-resolution image reconstruction

2005 ◽  
Vol 23 (7) ◽  
pp. 671-679 ◽  
Author(s):  
Di Zhang ◽  
Huifang Li ◽  
Minghui Du
Keyword(s):  
Image Reconstruction ◽  
Super Resolution ◽  
Resolution Image

A soft MAP framework for blind super-resolution image reconstruction

2009 ◽  
Vol 27 (4) ◽  
pp. 364-373 ◽  
Author(s):  
Yu He ◽  
Kim-Hui Yap ◽  
Li Chen ◽  
Lap-Pui Chau
Keyword(s):  
Image Reconstruction ◽  
Super Resolution ◽  
Resolution Image
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