Multi-scale image enhancement using a second derivative-like measure of contrast

Shahan Nercessian; Sos S. Agaian; Karen A. Panetta

doi:10.1117/12.906494

2 February 2012 Multi-scale image enhancement using a second derivative-like measure of contrast

Shahan Nercessian, Sos S. Agaian, Karen A. Panetta

Proceedings Volume 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II; 82950Q (2012) https://doi.org/10.1117/12.906494
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States

Abstract

Image enhancement algorithms attempt to improve the visual quality of images for human or machine perception. Most direct multi-scale image enhancement methods are based on enhancing either absolute intensity changes or the Weber contrast at each scale, and have the advantage that the visual contrast is enhanced in a controlled manner. However, the human visual system is not adapted to absolute intensity changes, while the Weber contrast is unstable for small values of background luminance and potentially unsuitable for complex image patterns. The Michelson contrast measure is a bounded measure of contrast, but its expression does not allow a straightforward direct image enhancement formulation. Recently, a second derivative-like measure of contrast has been used to assess the performance of image enhancement algorithms. This measure is a Michelson-like contrast measure for which a direct image enhancement algorithm can be formulated. Accordingly, we propose a new direct multi-scale image enhancement algorithm based on the SDME in this paper. Experimental results illustrate the potential benefits of the proposed algorithm.

Citation Download Citation

Shahan Nercessian, Sos S. Agaian, and Karen A. Panetta "Multi-scale image enhancement using a second derivative-like measure of contrast", Proc. SPIE 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II, 82950Q (2 February 2012); https://doi.org/10.1117/12.906494

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