Paper
23 September 2014 Digital deblurring based on linear-scale differential analysis
Vitali Bezzubik, Nikolai Belashenkov, Gleb V. Vdovin
Author Affiliations +
Abstract
A novel method of sharpness improvement is proposed for digital images. This method is realized via linear multi-scale analysis of source image and sequent synthesis of restored image. The analysis comprises the procedure of computation of intensity gradient values using the special filters providing simultaneous edge detection and noise filtering. Restoration of image sharpness is achieved by simple subtraction of some discrete recovery function from blurred image. Said recovery function is calculated as a sum of several normalized gradient responses found by linear multi-scale analysis using the operation of spatial transposition of those gradient response values relative the points of zero-crossing of first derivatives of gradients. The proposed method provides the restoration of sharpness of edges in digital image without additional operation of spatial noise filtering and a priori knowledge of blur kernel.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vitali Bezzubik, Nikolai Belashenkov, and Gleb V. Vdovin "Digital deblurring based on linear-scale differential analysis", Proc. SPIE 9217, Applications of Digital Image Processing XXXVII, 92170A (23 September 2014); https://doi.org/10.1117/12.2063378
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Cited by 1 scholarly publication.
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KEYWORDS
Silicon

Edge detection

Image analysis

Digital filtering

Image filtering

Convolution

Deconvolution

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