Enhancement of scanned documents in Besov spaces using wavelet domain representations

After scanning, a document is typically blurred, and some noise is introduced. Therefore, the enhancement process of a scanned document requires a denoising and deblurring step. Typically, these steps are performed using techniques originated in the Fourier-domain. It has been shown in many image processing applications such as compression and denoising that wavelet-domain processing outperforms Fourier-domain processing. One main reason for the success of wavelets is that wavelets adapt automatically to smooth and non-smooth parts in an image due to the link between wavelets and sophisticated smoothness spaces, the Besov spaces. Recently smoothing and sharpening of an image − interpreted as an increasing and decreasing of smoothness of an image − has been derived using Besov space properties. The goal of this paper is to use wavelet-based denoising and sharpening in Besov spaces in combination with characterization of lines and halftone patterns in the wavelet domain to build a complete wavelet-based enhancement system. It is shown that characteristics of a scanned document and the enhancement steps necessary for a digital copier application are well-suited to be modeled in terms of wavelet bases and Besov spaces. The modeling results leads to a very simple algorithmic implementation of a technique that qualitatively outperforms traditional Fourier-based techniques.