• Bayesian smoothing;
  • Chinese restaurant process;
  • Denoising;
  • Multiscale models

Summary.  We consider a multiscale model for intensities in photon-limited images using a Bayesian framework. A typical Dirichlet prior on relative intensities is not efficient in picking up structures owing to the continuity of intensities. We propose a novel prior using the so-called ‘Chinese restaurant process’ to create structures in the form of equal intensities of some neighbouring pixels. Simulations are conducted using several photon-limited images, which are common in X-ray astronomy and other high energy photon-based images. Applications to astronomical images from the Chandra X-ray Observatory satellite are shown. The new methodology outperforms most existing methods in terms of image processing quality, speed and the ability to select smoothing parameters automatically.