Some Good Reasons to Use Matched Filters for the Detection of Point Sources in CMB Maps

In this draft we comment on the results concerning the performances of matched filters, scale adaptive filters and Mexican hat wavelet that recently appeared in literature in the context of point source detection in Cosmic Microwave Background maps. In particular, we show that, contrary to what has been claimed, the use of the matched filters still appear to be the most reliable and efficient method to disantangle point sources from the backgrounds, even when using detection criterion that, differently from the classic $n\sigma$ thresholding rule, takes into account not only the height of the peaks in the signal corresponding to the candidate sources but also their curvature.Comment: Replacement after submission to A&A and referee's comments. Astronomy and Astrophysics, in press, JNL/2003/473

Integrating TV/digital data spectrograph system

A 25-mm vidicon camera was previously modified to allow operation in an integration mode for low-light-level astronomical work. The camera was then mated to a low-dispersion spectrograph for obtaining spectral information in the 400 to 750 nm range. A high speed digital video image system was utilized to digitize the analog video signal, place the information directly into computer-type memory, and record data on digital magnetic tape for permanent storage and subsequent analysis

Digital Deblurring of CMB Maps II: Asymmetric Point Spread Function

In this second paper in a series dedicated to developing efficient numerical techniques for the deblurring Cosmic Microwave Background (CMB) maps, we consider the case of asymmetric point spread functions (PSF). Although conceptually this problem is not different from the symmetric case, there are important differences from the computational point of view because it is no longer possible to use some of the efficient numerical techniques that work with symmetric PSFs. We present procedures that permit the use of efficient techniques even when this condition is not met. In particular, two methods are considered: a procedure based on a Kronecker approximation technique that can be implemented with the numerical methods used with symmetric PSFs but that has the limitation of requiring only mildly asymmetric PSFs. The second is a variant of the classic Tikhonov technique that works even with very asymmetric PSFs but that requires discarding the edges of the maps. We provide details for efficient implementations of the algorithms. Their performance is tested on simulated CMB maps.Comment: 9 pages, 13 Figure

Estimation of Regularization Parameters in Multiple-Image Deblurring

We consider the estimation of the regularization parameter for the simultaneous deblurring of multiple noisy images via Tikhonov regularization. We approach the problem in three ways. We first reduce the problem to a single-image deblurring for which the regularization parameter can be estimated through a classic generalized cross-validation (GCV) method. A modification of this function is used for correcting the undersmoothing typical of the original technique. With a second method, we minimize an average least-squares fit to the images and define a new GCV function. In the last approach, we use the classical $GCV$ on a single higher-dimensional image obtained by concatanating all the images into a single vector. With a reliable estimator of the regularization parameter, one can fully exploit the excellent computational characteristics typical of direct deblurring methods, which, especially for large images, makes them competitive with the more flexible but much slower iterative algorithms. The performance of the techniques is analyzed through numerical experiments. We find that under the independent homoscedastic and Gaussian assumptions made on the noise, the three approaches provide almost identical results with the first single image providing the practical advantage that no new software is required and the same image can be used with other deblurring algorithms.Comment: To appear in Astronomy & Astrophysic