Pixel recovery VIA ℓ 1 minimization in the wavelet domain

Ivan W. Selesnick, Richard Van Slyke, Onur G. Guleryuz

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper uses probability models on expansive wavelet transform coefficients with interpolation constraints to estimate missing blocks in images. We use simple probability models on wavelet coefficients to formulate the estimation process as a linear programming problem and solve it to recover the missing pixels. Our formulation is general and can be augmented with more sophisticated probability models to obtain even better estimates on a variety of image regions. The presented approach has many parallels to recently introduced dictionary based signal representations with which it shares certain optimality properties. We provide simulation examples over edge regions using both critically-sampled and expansive (over-complete) wavelet transforms.

Original languageEnglish (US)
Title of host publication2004 International Conference on Image Processing, ICIP 2004
Number of pages4
StatePublished - 2004
Event2004 International Conference on Image Processing, ICIP 2004 - , Singapore
Duration: Oct 18 2004Oct 21 2004

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880


Other2004 International Conference on Image Processing, ICIP 2004

ASJC Scopus subject areas

  • Engineering(all)


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