Peak signal-to-blur ratio (PSBR) is a recently introduced measure of detail preservation that aims at overcoming the limitations of the sole peak signal-to-noise ratio (PSNR) and other metrics in evaluating the performance of image denoising filters. Indeed, it is known that image denoising is not a trivial task: the image details should be preserved during noise removal, so accurate measurements of the filtering features are needed in order to validate new filters. This paper presents a novel algorithm for PSBR evaluation that is computationally lighter and more effective than the previous PSBR technique. In particular, the new algorithm does not require any threshold and does not need any offset-correction procedure. Results of computer simulations dealing with images corrupted by Gaussian and impulse noise show that the proposed PSBR yields very accurate measurements and largely outperforms the previous approach and other metrics in the literature.
