دانلود رایگان مقاله تشخیص و حذف آرتیفکت در تصاویر نجومی

ABSTRACT

Astronomical images from optical photometric surveys are typically contaminated with transient artifacts such as cosmic rays, satellite trails and scattered light. We have developed and tested an algorithm that removes these artifacts using a deep, artifact free, static sky coadd image built up through the median combination of point spread function (PSF) homogenized, overlapping single epoch images. Transient artifacts are detected and masked in each single epoch image through comparison with an artifact free, PSF-matched simulated image that is constructed using the PSF-corrected, model fitting catalog from the artifact free coadd image together with the position variable PSF model of the single epoch image. This approach works well not only for cleaning single epoch images with worse seeing than the PSF homogenized coadd, but also the traditionally much more challenging problem of cleaning single epoch images with better seeing. In addition to masking transient artifacts, we have developed an interpolation approach that uses the local PSF and performs well in removing artifacts whose widths are smaller than the PSF full width at half maximum, including cosmic rays, the peaks of saturated stars and bleed trails. We have tested this algorithm on Dark Energy Survey Science Verification data and present performance metrics. More generally, our algorithm can be applied to any survey which images the same part of the sky multiple times.

7. Conclusions

We have developed an automated masking algorithm for the detection of all transient artifacts typically found in astronomical images. These artifacts include non-imaged artifacts such as cosmic rays as well as imaged artifacts like satellite trails and scattered light. This algorithm uses the multiple images of each portion of the sky to build a model of the non-varying or persistent light distribution of both resolved and unresolved sources, and therefore a requirement for this algorithm is that the dataset includes multiple images of each sky location. The algorithm builds the persistent light distribution through the median combination of PSF homogenized single epoch images into a coadd image with a well behaved (typically spatially invariant) PSF. Then PSF corrected model fitting to the light distribution is carried out using SExtractor. The resulting coadd catalog is used together with the single epoch image PSF model to construct a single epoch model image. Deviations between the observed light distribution in the single epoch image and the model image then indicate pixels that are affected by artifacts. These artifacts can be identified whether or not they overlap real objects. A small fraction of the image pixels (<0.5%) cannot be used to identify artifacts because of failures in the model fitting to the PSF homogenized coadd images. Thus, our algorithm automatically identifies and masks artifacts in >99.5% of the single epoch image pixels.