Abstract
Underwater Target Detecting is an Important Technique for the Development of the Ocean Engineering and Exploration Also a Significant Task of the Ocean Detecting. It Plays a Substantial Role Not Only for the Civil Economy but Also for the National Security. the Formation of the Super-Resolution Underwater Image is Significant Topic in Ocean Detecting Field. in Order to Enhance the Visual Quality of Images Obtained by Underwater Imaging Systems, Super Resolution (Sr) Reconstruction is Introduced, Including Single-Frame and Multi-Frame Sr Algorithms. Real-World Images Often Contain Singularities Such as Edges and High-Frequency Textured Regions. as a Result, These Methods Suffer from Various Edge-Related Visual Artifacts Such as Ringing, Aliasing, Jagging, and Blurring We Mainly Focus on Super-Resolution from Single Low Resolution Input Image. the Goal of Single Image Super-Resolution is to Estimate a High-Resolution Image from a Low-Resolution Input. in This Paper, We Propose a New High-Quality and Efficient Single-Image Upscaling Technique.
Recommended Citation
X. Wang et al., "Underwater Image Super-Resolution Reconstruction with Local Self-Similarity Analysis and Wavelet Decomposition," OCEANS 2017 - Aberdeen, pp. 1 - 6, Institute of Electrical and Electronics Engineers, Oct 2017.
The definitive version is available at https://doi.org/10.1109/OCEANSE.2017.8084745
Department(s)
Engineering Management and Systems Engineering
Keywords and Phrases
self-similarity; super-resolution; wavelet decomposition
International Standard Book Number (ISBN)
978-150905278-3
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
25 Oct 2017
