An Analysis of Image Denoising and Restoration of Handwritten Degraded Document Images

The restoration of a blurry or noisy image is commonly performed with a MAP estimator, which maximizes a posterior probability to reconstruct a clean image from a degraded image. A MAP estimator, when used with a sparse gradient image prior, reconstructs piecewise smooth images and typically removes textures that are important for visual realism. The three public datasets that were used in the recent. Document Image Binarization Contest (DIBCO) 2009 & 2011 and Handwritten Document Image Binarization Contest (H-DIBCO) 2010 and achieves different accuracies. Experiments on the Bickley diary dataset that consists of several challenging bad quality document images also show the superior performance in image binarization technique which is compared with different techniques. The general objective is to identify current advantages in document image binarization using established evaluation performance measures. Keywords— Image Processing, Pixel Classification, Degraded Document, Image Binarization, Adaptive Image Contrast