Effective document image deblurring via gradient histogram preservation
Traditional deblurring algorithms are often focused on natural-scaled images, which are not adapted for document texts and images without having some negative impacts on the accuracy of the OCR and the visual quality. In this paper, we propose a gradient histogram preservation method. An effective optimization method was developed and achieves satisfying results for kernel estimation. By combining the gradient histogram preservation prior with conventional image deblurring methods, it significantly improves the simulations and experimental results on document images and a high SSIM is achieved with the proposed method.