Wavelet-domain blur invariants for image analysis.

Radiometric degradation is a common problem in the image acquisition part of many applications. There is much research carried out in an effort to deblur such images. However, it has been proven that it is not always necessary to go through a burdensome process of deblurring. To tackle this problem, different blur-invariant descriptors have been proposed so far, which are either in the spatial domain or based on the properties available in the Fourier domain. In this paper, wavelet-domain blur invariants are proposed for the first time for discrete 2-D signals. These descriptors, which are invariant to centrally symmetric blurs, inherit the advantages that this domain provides. It is also proven that the spatial-domain blur invariants are a special version of the proposed invariants. The performance of these invariants will be demonstrated through experiments.