Adaptive-neighborhood image deblurring

Moment-preserving sharpening - A new approach to digital picture deblurring

A new approach to sharpening blurred pictures using the moment-preserving principle is proposed. The new gray value assigned to each pixel in the desired picture is computed deterministically in such a way that the moments of the n x n neighborhood of the pixel are preserved. The selection of the neighborhood size n depends on the blurring degree of the picture. The sharpening operation can als...

Improved image deblurring based on salient-region segmentation

Image deblurring techniques play important roles in many image processing applications. As the blur varies spatially across the image plane, it calls for robust and effective methods to deal with the spatially-variant blur problem. In this paper, a Saliency-based Deblurring (SD) approach is proposed based on the saliency detection for salient-region segmentation and a corresponding compensate m...

Adaptive Varying Scale Methods in Image Processing Part I: Denoising and Deblurring

Adaptive Motion Detection for Image Deblurring in RTS Controller

An Adaptive method for Image Deblurring is presented here. Processing of image data collected from both surveillance camera and on road traffic control motor vehicle camera is a big issue because often the objects are in motion and sometimes both the objects and camera are not steady. This leads to Blurring of the image and further image processing is not possible due to the degradation of rece...

Non-uniform Single Image Deblurring Based on Sparse Representation and Adaptive Dictionary Learning

Considering the sparseness property of images, a sparse representation based iterative deblurring method is presented for single image deblurring under uniform and non-uniform motion blur. The approach taken is based on sparse and redundant representations over adaptively training dictionaries from single blurred-noisy image itself. Further, the K-SVD algorithm is used to obtain a dictionary th...