Multiscale distilled sensing: A source detection method for infrared and radio astronomical images

Astronomical images are characterized by having a high component of noise, a non-homogeneous background, and a great number of sources (objects) difficult to identify even by experts. All these factors are especially remarkable in high wavelength images such as infrared and radio. Hence, great efforts have been done to solve the automatic detection of sources in this type of images. In this paper, we propose a new approach based on multiscale decomposition and the recently developed Distilled Sensing method. Their combined use allows the minimization of the complex background effects as well as the highlighting of the sources. The experimental results obtained using public infrared and radio images demonstrate the validity of the approach, detecting a greater number of true sources than the original Distilled Sensing and the well-known SExtractor algorithm.