Fundamentals of digital image processing
Fundamentals of digital image processing
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Fields of Experts: A Framework for Learning Image Priors
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Identification of parameters and restoration of motion blurred images
Proceedings of the 2006 ACM symposium on Applied computing
Wavelet-based deconvolution for ill-conditioned systems
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06
Enhancing photographs using content-specific image priors
Enhancing photographs using content-specific image priors
A Taxonomy for Noise in Images of Paper Documents - The Physical Noises
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
Automatically detecting and classifying noises in document images
Proceedings of the 2010 ACM Symposium on Applied Computing
Motion blur identification in noisy images using feed-forward back propagation neural network
IWICPAS'06 Proceedings of the 2006 Advances in Machine Vision, Image Processing, and Pattern Analysis international conference on Intelligent Computing in Pattern Analysis/Synthesis
Correcting book binding distortion in scanned documents
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
Blur identification using the bispectrum
IEEE Transactions on Signal Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
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Document images may exhibit some blurred areas due to a wide number of reasons ranging from digitalization, filtering or even storage problems. Most de-blurring algorithms are hard to implement, slow, and often try to be general, attempting to remove the blur in any kind of image. In the case of text document images, the transition between characters and the paper background has a high contrast. With that in mind, a new algorithm is proposed for de-blurring of textual documents; there is no need to estimate the PSF and the filter proposed can be directed applied to the image. The presented algorithm reached an improvement rate of 17.08% in the SSIM metric.