ABSTRACT-Processing blurred images is a key problem in many image applications. Existing methods to obtain blur invariants which are invariant with respect to centrally symmetric blur are based on geometric moments or complex moments. In this paper, we propose a new method to construct a set

Abstract—Processing blurred images is a key problem in many image applications. Existing methods to obtain blur invariants which are invariant with respect to centrally symmetric blur are based on geometric moments or complex moments. In this paper, we propose a new method to construct a set

from the previous frames. Blurred but otherwise unchanged areas of the images are recognized using blur invariant features. A statis-tical approach for calculating the weights for the blur invariant features in frequency and spatial domains is also proposed, and compared to the unweighted invariants

In this paper, we propose novel blur and similarity trans-form (i.e. rotation, scaling and translation) invariant fea-tures for the recognition of objects in images. The features are based on blur invariant forms of the log-polar sampled phase-only bispectrum and are invariant to centrally sym

Processing blurred images is a key problem in many image applications. Existing methods to obtain blur invariants which are invariant with respect to centrally symmetric blur are based on geometric moments or complex moments. In this paper, we propose a new method to construct a set of blur

Image registration is a classical problem in remotely sensed image analysis. In this paper, attention is paid to control point matching in case the images are blurred and rotated one another. The matching is performed by means of a new class of moment invariants, which are calculated over

to similarity transformation and to convolution with spread spectrum(PSF). In this mainly two contributions are provided, The frame work for theoretical is derived from Zernike moments of a blurred image and the way to construct the one of invariant moment combined geometric blur invariants. To evaluate

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

We demonstrate that image stabilizing hardware included in many camera lenses can be used to implement motion invariance and custom blur effects. Motion invariance is intended to capture images where objects within a range of velocities appear defocused with the same point spread function

Abstract. We propose a novel approach for estimating a depth-map from a pair of rectified stereo images degraded by blur and contrast change. At each location in image space, information is encoded with a new class of descriptors that are invariant to convolution with centrally symmetric PSF