Dark Frame Correction Via Bayesian Estimator in the Wavelet Domain

• Published in: 2006 IEEE International Symposium on Signal Processing and Information Technology pp. 55 - 58
• Main Authors: Svihlik, J., Pata, P.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-08-2006
• Subjects: Bayesian estimator; Bayesian methods; Charge coupled devices; Charge-coupled image sensors; Dark current; dark frame correction; generalized Laplacian; Image databases; Laplace equations; Least squares approximation; Probability density function; statistical model of the probability density function; Wavelet coefficients; Wavelet domain; wavelet transform
• DOI: 10.1109/ISSPIT.2006.270769
• ISBN: 0780397533; 9780780397538
• ISSN: 2162-7843

It is generally known that every astronomical image which was acquired by a CCD sensor, have to be corrected by the dark frame. The dark frame maps the dark current of the CCD. If we don't have the dark frame, we cannot directly correct the astronomical images. This work deals with dark frame correction based on Bayesian estimator in the wavelet domain. The models of the marginal probability density function (PDF) of the wavelet coefficients of astronomical images and dark frame images based on generalized Laplacian is used by this estimator. The parameters of the models, which were mentioned above, were estimated by the least square error method on the set of images from our image database. The correction of the astronomical images by dark frame is better than the Bayesian estimator, but further work deals with more sophisticated Bayesian estimators with more robust statistical description of the images