A New Image Denoising Algorithm that Preserves Structures of Astronomical Data

Details A New Image Denoising Algorithm that Preserves Structures of Astronomical Data A New Image Denoising Algorithm that Preserves Structures of Astronomical Data

May 2007

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007aas...210.7609b&link_type=abstract

American Astronomical Society Meeting 210, #76.09; Bulletin of the American Astronomical Society, Vol. 39, p.184

Astronomy and Astrophysics

Astronomy

Scientific paper

We have processed numerous x-ray data sets using several well-known algorithms such as Gaussian and adaptive smoothing for public related image releases. These algorithms are used to denoise/smooth images and retain the overall structure of observed objects. Recently, a new PDE algorithm and program, provided by Dr. David Tschumperle and referred to as GREYCstoration, has been tested and is in the progress of being implemented into the Chandra EPO imaging group.
Results of GREYCstoration will be presented and compared to the currently used methods for x-ray and multiple wavelength images. What demarcates Tschumperle's algorithm from the current algorithms used by the EPO imaging group is its ability to preserve the main structures of an image strongly, while reducing noise. In addition to denoising images, GREYCstoration can be used to erase artifacts accumulated during observation and mosaicing stages.
GREYCstoration produces results that are comparable and in some cases more preferable than the current denoising/smoothing algorithms. From our early stages of testing, the results of the new algorithm will provide insight on the algorithm's initial capabilities on multiple wavelength astronomy data sets.

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