Blind deconvolution of two-dimensional complex data
Inspired by the work of Lane and Bates on automatic multidimensional deconvolution, the authors have developed a systematic approach and an operational code for performing the deconvolution of multiply-convolved two-dimensional complex data sets in the absence of noise. They explain, in some detail, the major algorithmic steps, where noise or numerical errors can cause problems, their approach in dealing with numerical rounding errors, and where special noise-mitigating techniques can be used toward making blind deconvolution practical. Several examples of deconvolved imagery are presented, and future research directions are noted.
- Research Organization:
- Sandia National Labs., Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 10127824
- Report Number(s):
- SAND--92-1706; ON: DE94007254; BR: GB0103012
- Country of Publication:
- United States
- Language:
- English
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