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Jan Flusser, Tomás Suk, "Degraded Image Analysis: An Invariant Approach," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 6, pp. 590603, June, 1998.  
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@article{ 10.1109/34.683773, author = {Jan Flusser and Tomás Suk}, title = {Degraded Image Analysis: An Invariant Approach}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {20}, number = {6}, issn = {01628828}, year = {1998}, pages = {590603}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.683773}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  Degraded Image Analysis: An Invariant Approach IS  6 SN  01628828 SP590 EP603 EPD  590603 A1  Jan Flusser, A1  Tomás Suk, PY  1998 KW  Degraded image KW  symmetric blur KW  blur invariants KW  image moments KW  combined invariants KW  object recognition. VL  20 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
Abstract—Analysis and interpretation of an image which was acquired by a nonideal imaging system is the key problem in many application areas. The observed image is usually corrupted by blurring, spatial degradations, and random noise. Classical methods like blind deconvolution try to estimate the blur parameters and to restore the image. In this paper, we propose an alternative approach. We derive the features for image representation which are invariant with respect to blur regardless of the degradation PSF provided that it is centrally symmetric. As we prove in the paper, there exist two classes of such features: the first one in the spatial domain and the second one in the frequency domain. We also derive socalled combined invariants, which are invariant to composite geometric and blur degradations. Knowing these features, we can recognize objects in the degraded scene without any restoration.
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