Edge Localized Image Sharpening via Reassignment with Application to Computed Tomography

Timothy Dorney (tdorney@ieee.org)
Electrical and Computer Engineering, Rice University

Srikrishna Bhashyam (skrishna@rice.edu)
Electrical and Computer Engineering, Rice University

Andrew Doran (awd@zai.com)
Zeta Associates Incorporated

Hyeokho Choi (choi@ece.rice.edu)
Electrical and Computer Engineering, Rice University

Patrick Flandrin (flandrin@ens-lyon.fr)
Ecole Normale Supérieure de Lyon, Laboratoire de Physique (UMR 5672 CNRS), 46 allée d'Italie 69364 Lyon Cedex 07, France

Richard Baraniuk (richb@rice.edu)
Electrical and Computer Engineering, Rice University

Abstract

Traditional filtering methods operate on the entire signal or image. In some applications, however, errors are concentrated in specific regions or features. A prime example is images generated using computed tomography. Practical implementations limit the amount of high frequency content in the reconstructed image, and consequently, edges are blurred. We introduce a new post-reconstruction edge enhancement algorithm, based on the reassignment principle and wavelets, that localizes its sharpening exclusively to edge features. Our method enhances edges without disturbing the low frequency textural details.

MATLAB® Code and Images

Main program that contains all the MATLAB® code (tdorney_main.m).
The original phantom with 512x512 pixels stored in the MATLAB® file format (tdorney_img_orig_512.mat). Please right-click to save to a file.
The reconstructed phantom with 512x512 pixels, 800 projection angles, 1000 rays, and a 1.5 normalized detector length (tdorney_reconst_image_800_1.5_1000_512.mat). Please right-click to save to a file.