Relative intersection of confidence intervals rule for sharper restoration of soft x-ray images

Abstract

We present a novel method for restoration of images of nanostructures obtained with a soft-ray microscope that uses a 46.9 nm soft x-ray laser microscope for illumination. To suppress the noise and to preserve the image sharpness, we develop a method based on pixel adaptive zero-order modeling of the observed object. Neighboring areas of each pixel are selected using the relative intersection of confidence intervals rule and used for restoration. Due to the non-uniform distribution of noise in the images, we use robust spatial noise modeling. The method provides sharp restored images—sharper than competitive approaches. The sharpness is measured using local phase coherence in the complex wavelet transform domain and shows visible improvement of the novel method.

© 2016 Optical Society of America

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