This paper presents an algorithm for detection and localization of blurred regions in images. The algorithm is based on discrimination of the gradient distributions between blurred and non-blurred image regions. For this purpose, global wavelet transform of Y component of the image is applied, and the obtained wavelet map is divided into overlapping patches. Then a trained probabilistic SVM classifier estimates the blur level of the patches on their wavelet gradient histograms and thereby probability map is constructed. Finally, we perform a more precise determination of borders of blur region based on estimated Laplace distribution of its wavelet coefficients.

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