Abstract

We propose a notion of double discrete wavelet transform (DDWT) that is designed to sparsify the blurred image and the blur kernel simultaneously. DDWT greatly enhances our ability to analyze, detect, and process blur kernels and blurry images, and we present example applications in blur kernel estimation, deblurring, and near-blur-invariant image feature extraction.

© 2013 Optical Society of America