Psychovisually-based multiresolution image segmentation

Psychophysical studies have shown that there are three image components of distinct perceptual significance to human observers: strong edges, smooth regions, and textured or detailed regions. A psychophysical test was performed to evaluate the perceptual role of each region and a segmentation algorithm was developed to segment an image into the three regions. The segmentation algorithm identifies blocks of an image as belonging to one of the perceptual regions by analyzing high frequency coefficients of a 3-level hierarchical subband/wavelet decomposition. The segmentation algorithm performs well on a wide range of image content, including natural images and mixed images containing text, graphics, and natural scenes.

[1]  Sheila S. Hemami,et al.  Robust image coding with perceptual-based scalability , 1997, Proceedings DCC '97. Data Compression Conference.

[2]  K. Fieandt,et al.  The perceptual world , 1977 .

[3]  I. Rock The Perceptual world: readings from Scientific American magazine , 1990 .

[4]  Peter N. Heller,et al.  Smoothness-constrained wavelet image compression , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[5]  Nasser M. Nasrabadi,et al.  Edge-based subband VQ techniques for images and video , 1994, IEEE Trans. Circuits Syst. Video Technol..

[6]  Stéphane Mallat,et al.  Characterization of Signals from Multiscale Edges , 2011, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Sanjit K. Mitra,et al.  A technique for the efficient coding of the upper bands in subband coding of images , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[8]  Nariman Farvardin,et al.  A perceptually motivated three-component image model-Part I: description of the model , 1995, IEEE Trans. Image Process..

[9]  Y. Meyer Wavelets and Operators , 1993 .