Authors:
Florian Brusius
;
Ulrich Schwanecke
and
Peter Barth
Affiliation:
Hochschule RheinMain, Germany
Keyword(s):
Image processing, Blind deconvolution, Image restoration, Deblurring, Motion blur estimation, Barcodes, Mobile devices, Radon transform.
Related
Ontology
Subjects/Areas/Topics:
Camera Phones and Mobile Imaging
;
Computer Vision, Visualization and Computer Graphics
;
Digital Image Processing
;
Image and Video Analysis
;
Image Enhancement and Restoration
;
Image Formation and Preprocessing
;
Spectral Image Capture, Processing, and Analysis
Abstract:
In this paper, a new method for the identification and removal of image artifacts caused by linear motion blur is presented. By transforming the image into the frequency domain and computing its logarithmic power spectrum, the algorithm identifies the parameters describing the camera motion that caused the blur. The spectrum is analysed using an adjusted version of the Radon transform and a straightforward method for detecting local minima. Out of the computed parameters, a blur kernel is formed, which is used to deconvolute the image. As a result, the algorithm is able to make previously unrecognisable features clearly legible again. The method is designed to work in resource-constrained environments, such as on mobile devices, where it can serve as a preprocessing stage for information recognition software that uses the camera as an additional input device.