Enhancement of document images from cameras

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 3305, Issue , 1998, Pages 230-241

  Taylor, M J ^a   Dance, C R ^a  

^a Xerox Research Centre Europe   (United States)

Author keywords

Digital cameras; Image restoration; OCR; Scanning; Thresholding

Indexed keywords

ALGORITHMS; CAMERAS; COLOR IMAGE PROCESSING; IMAGE QUALITY; INTERPOLATION; OPTICAL CHARACTER RECOGNITION; PHOTOGRAPHY; SCANNING;

DEBLURRING; DIGITAL CAMERAS; DOCUMENT IMAGES; PIXEL; RESOLUTION ENHANCEMENT; SCANNING CAPABILITY;

IMAGE ENHANCEMENT;

EID: 0032224338     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.304635     Document Type: Conference Paper

References (31)

1. A new method for image segmentation
2. Interacting with paper on the digital desk
3. Student readers' use of library documents: Implications for digital library technologies
4. A desk supporting computer-based interaction with paper documents
5. Iterative methods for image deblurring
6. Blur identification by residual spectral matching
7. Blind image deconvolution
8. Maximum likelihood image and blur identification: A unifying approach
9. Identification and restoration of noisy blurred images using the expectation-maximisation algorithm
10. A regularisation approach to joint blur identification and image restoration
11. PSF estimation for image deblurring
12. Robust identification of motion and out-of-focus blur parameters from blurred and noisy images
13. Blur identification by the method of generalized cross-validation
14. Goal-directed evaluation of binarization methods
15. A survey of thresholding techniques
16. Graphics image coding for freeze-frame videoconferencing
17. Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images
18. Restoration of binary images using stochastic relaxation with annealing
19. Direct gray-scale extraction of features for character recognition
20. Survey of recent developments in digital image restoration
21. Methods for choosing the regularisation parameter and estimating the noise variance in image restoration and their relation
22. Discontinuity preserving regularisation of inverse problems
23. A Bayesian approach to image expansion for improved definition
24. Regularised iterative image restoration with ringing reduction
25. Image restoration based on a subjective criterion