Image deblurring is a classic problem in low-level computer vision with the aim to recover a
sharp image from a blurred input image. Advances in deep learning have led to significant …

This paper comprehensively reviews the recent development of image deblurring, including
non-blind/blind, spatially invariant/variant deblurring techniques. Indeed, these techniques …

We present a simple and effective blind image deblurring method based on the dark
channel prior. Our work is inspired by the interesting observation that the dark channel of …

We present an effective blind image deblurring algorithm based on the dark channel prior.
The motivation of this work is an interesting observation that the dark channel of blurred …

We propose a simple yet effective L_0-regularized prior based on intensity and gradient for
text image deblurring. The proposed image prior is motivated by observing distinct …

We propose a simple yet effective L 0-regularized prior based on intensity and gradient for
text image deblurring. The proposed image prior is based on distinctive properties of text …

We consider how image super-resolution (SR) can contribute to an object detection task in
low-resolution images. Intuitively, SR gives a positive impact on the object detection task …

Documents often exhibit various forms of degradation, which make it hard to be read and
substantially deteriorate the performance of an OCR system. In this paper, we propose an …

In this work we address the problem of blind deconvolution and denoising. We focus on
restoration of text documents and we show that this type of highly structured data can be …

Document image enhancement methods are often used to improve the accuracy and
efficiency of automated document analysis and recognition tasks such as character …