Abstract
Enhancement of degraded images of binary shapes is an important task in many image processing applications, e.g. to provide appropriate image quality for optical character recognition. Although many image restoration methods can be found in the literature, most of them are developed for grayscale images. In this paper we propose a novel binary image restoration algorithm. As a first step, it restores the projections of the shape using 1-dimensional deconvolution, then reconstructs the image from these projections using a discrete tomography technique. The method does not require any parameter setting or prior knowledge like an estimation of the signal-to-noise ratio. Numerical experiments on a synthetic dataset show that the proposed algorithm is robust to the level of the noise. The efficiency of the method has also been demonstrated on real out-of-focus alphanumeric images.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-3-319-02895-8_64
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Nemeth, J., Balazs, P. (2013). Restoration of Blurred Binary Images Using Discrete Tomography. In: Blanc-Talon, J., Kasinski, A., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2013. Lecture Notes in Computer Science, vol 8192. Springer, Cham. https://doi.org/10.1007/978-3-319-02895-8_8
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DOI: https://doi.org/10.1007/978-3-319-02895-8_8
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