Efficient restoration and enhancement of super-resolved X-ray images

Our previous work demonstrates the ability to reconstruct a single higher resolution image from fusing a collection of multiple extremely low-dosage aliased X-ray images. While this computationally efficient method eliminates aliasing artifacts associated with undersampling, it does not address the problem of deblurring the reconstructed image. In this paper, we present a fast nonlinear deblurring algorithm, specifically designed to address the nonstationary noise associated with multiframe reconstructed images. The algorithm uses a combination of Fourier sharpening and wavelet denoising similar to the ForWarD algorithm. Experimental results on enhancing digital mammogram images attest to the effectiveness of the presented method.