When we perform a visual analysis of a cosmic object photograph the contrast plays a fundamental role. A linear distribution of the observable values is not necessarily the best possible for the Human Visual System (HVS). In fact HVS has a non-linear response, and exploits contrast locally with different stretching for different lightness areas. As a consequence, according to the observation task, local contrast can be adjusted to make easier the detection of relevant information. The proposed approach is based on Spatial Color Algorithms (SCA) that mimic the HVS behavior. These algorithms compute each pixel value by a spatial comparison with all (or a subset of) the other pixels of the image. The comparison can be implemented as a weighted difference or as a ratio product over given sampling in the neighbor region. A final mapping allows exploiting all the available dynamic range. In the case of color images SCA process separately the three chromatic channels producing an effect of color normalization, without introducing channel cross correlation. We will present very promising results on amateur photographs of deep sky objects. The results are presented for a qualitative and subjective visual evaluation and for a quantitative evaluation through image quality measures, in particular to quantify the effect of algorithms on the noise. Moreover our results help to better characterize contrast measures.

Date Published: 8 August 2016
PDF: 10 pages
Proc. SPIE 9913, Software and Cyberinfrastructure for Astronomy IV, 99134P (8 August 2016); doi: 10.1117/12.2230895

Published in SPIE Proceedings Vol. 9913:
Software and Cyberinfrastructure for Astronomy IV
Gianluca Chiozzi; Juan C. Guzman, Editor(s)