Back to Search
Start Over
Resolution enhancement of textual images: a survey of single image-based methods
- Source :
- IET Image Processing, IET Image Processing, Institution of Engineering and Technology, 2016, Volume 10 (Issue 4), p. 325-337. ⟨10.1049/iet-ipr.2015.0334⟩
- Publication Year :
- 2016
- Publisher :
- HAL CCSD, 2016.
-
Abstract
- International audience; Super-resolution (SR) task has become an important research area due to the rapidly growing interest for high quality images in various computer vision and pattern recognition applications. This has led to the emergence of various SR approaches. According to the number of input images, two kinds of approaches could be distinguished: single or multi-input based approaches. Certainly, processing multiple inputs could lead to an interesting output, but this is not the case mainly for textual image processing. This study focuses on single image-based approaches. Most of the existing methods have been successfully applied on natural images. Nevertheless, their direct application on textual images is not enough efficient due to the specificities that distinguish these particular images from natural images. Therefore, SR approaches especially suited for textual images are proposed in the literature. Previous overviews of SR methods have been concentrated on natural images application with no real application on the textual ones. Thus, this study aims to tackle this lack by surveying methods that are mainly designed for enhancing low-resolution textual images. The authors further criticise these methods and discuss areas which promise improvements in such task. To the best of the authors’ knowledge, this survey is the first investigation in the literature.
- Subjects :
- Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Image processing
02 engineering and technology
[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]
computer vision
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Digital image
Image texture
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Digital image processing
0202 electrical engineering, electronic engineering, information engineering
Computer vision
image enhancement
image texture
Electrical and Electronic Engineering
Image analysis
Image resolution
Feature detection (computer vision)
Information retrieval
business.industry
[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]
[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
020207 software engineering
[INFO.INFO-TT]Computer Science [cs]/Document and Text Processing
Automatic image annotation
image recognition
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
Signal Processing
020201 artificial intelligence & image processing
Computer Vision and Pattern Recognition
Artificial intelligence
business
Software
image resolution
Subjects
Details
- Language :
- English
- ISSN :
- 17519659 and 17519667
- Database :
- OpenAIRE
- Journal :
- IET Image Processing, IET Image Processing, Institution of Engineering and Technology, 2016, Volume 10 (Issue 4), p. 325-337. ⟨10.1049/iet-ipr.2015.0334⟩
- Accession number :
- edsair.doi.dedup.....6607a3ecbc1dfa52a1a31dc1a5ef3e4e