An a-contrario approach to quasi-periodic noise removal

International audienceImages can be affected by quasi-periodic noise. This undesirable feature manifests itself by spurious repetitive patterns covering the whole image, well localized in the Fourier domain. While notch filtering permits to get rid of this phenomenon , this however requires to first detect the resulting Fourier spikes, and, in particular, to discriminate between noise spikes and spectrum patterns caused by spatially localized textures or repetitive structures. This paper proposes a statistical a-contrario detection of noise spikes in the Fourier domain. A Matlab code is also provided

An a contrario approach for parameters estimation of a motion blurred image

International audienceThe recovery of a motion-blurred image is an important ill-posed inverse problem. But this subject has not recently received lot of attention. We propose a probabilistic method for the estimation of motion parameters based on the geometrical characteristic of the Fourier spectrum. Indeed, the Fourier spectrum of the blurred image is made by the product of the original Fourier spectrum with an oriented cardinal sine function. The estimation of the parameters reduces to the detection of the direction and of the gap between oscillations of the Fourier spectrum. Using the Helmholtz principle, the maximum meaningful parallel alignments are detected in the frequency domain, and then the direction and the extent of the blur are identified by an adapted K-means cluster algorithm. Simulation results show that the approach is very promising