This paper introduces a very low complexity visual masking algorithm for the JPEG2000 image compression standard and evaluates its impact on the visual image quality by means of the Multi-scale SSIM index. The algorithm derives suitable weighting masks indirectly from a statistical model of the wavelet data which is defined from the second moment and the average absolute amplitude of the data. If combined with an a priori rate allocation algorithm, the computation of the visual masking weights has almost no overhead at all.
Index Terms:
JPEG2000, Visual Masking, Generalized Gaussian
Citation:
Thomas Richter, "Effective Visual Masking Techniques in JPEG2000," dcc, pp.540, Data Compression Conference (dcc 2008), 2008