Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers (1994)
Pacific Grove, CA, USA
Oct. 31, 1994 to Nov. 2, 1994
I. Hussain , Dept. of Electr. & Comput. Eng., California Univ., Davis, CA, USA
T.R. Reed , Dept. of Electr. & Comput. Eng., California Univ., Davis, CA, USA
This paper presents a method to preprocess an image so that when segmented it yields a partitioning in which textured regions are approximated with a substantially reduced number of uniform regions (which is desirable for the coding). The segmentation method used to form this representation combines a Gaussian texture model and Gibbs-Markov contour model in order to find regions with boundaries which correspond closely to the objects in the image. Given the image segmentation, an approximation to the original image is generated by filling each region with its mean value. If higher quality reconstruction is desired, the quantized approximation error is also encoded. In order to exploit the reduced sensitivity of the human visual system to the error around edges (visual masking), the error is quantized using three nonlinear quantizers corresponding to the smoothly varying, textured, and remaining areas of the image, respectively.<
image texture, image segmentation, image enhancement, image coding, data compression, quantisation (signal), coding errors, error statistics, Markov processes, image reconstruction
I. Hussain and T. Reed, "Segmentation-based image compression with enhanced treatment of textured regions," Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers(ACSSC), Pacific Grove, CA, USA, 1995, pp. 965-969.