Paper
3 March 2008 Deblurring noisy radial-blurred images: spatially adaptive filtering approach
Author Affiliations +
Proceedings Volume 6812, Image Processing: Algorithms and Systems VI; 68121D (2008) https://doi.org/10.1117/12.769400
Event: Electronic Imaging, 2008, San Jose, California, United States
Abstract
The deblurring of images corrupted by radial blur is studied. This type of blur appears in images acquired during an any camera translation having a substantial component orthogonal to the image plane. The point spread functions (PSF PSF) describing this blur are spatially varying. However, this blurring process does not mix together pixels lying on differen different radial lines, i.e. lines stemming from a unique point in the image, the so called "blur center". Thus, in suitable pola polar coordinates, the blurring process is essentially a 1-D linear operator, described by the multiplication with the blurrin blurring matrix. We consider images corrupted simultaneously by radial blur and noise. The proposed deblurring algorithm is base based on two separate forms of regularization of the blur inverse. First, in the polar domain, we invert the blurring matri matrix using the Tikhonov regularization. We then derive a particular modeling of the noise spectrum after both the regularize regularized inversion and the forward and backward coordinate transformations. Thanks to this model, we successfully use a denoisin denoising algorithm in the Cartesian domain. We use a non-linear spatially adaptive filter, the Pointwise Shape-Adaptive DCT, i in order to exploit the image structures and attenuate noise and artifacts. Experimental results demonstrate that the proposed algorithm can effectively restore radial blurred images corrupted by additive white Gaussian noise.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Giacomo Boracchi, Alessandro Foi, Vladimir Katkovnik, and Karen Egiazarian "Deblurring noisy radial-blurred images: spatially adaptive filtering approach", Proc. SPIE 6812, Image Processing: Algorithms and Systems VI, 68121D (3 March 2008); https://doi.org/10.1117/12.769400
Lens.org Logo
CITATIONS
Cited by 7 scholarly publications and 1 patent.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Cameras

Point spread functions

Denoising

Image processing

Image filtering

Digital filtering

Nonlinear filtering

Back to Top