Object-based image segmentation using DWT/RDWT multiresolution Markov Random Field Conference Paper uri icon

abstract

  • This paper introduces a segmentation algorithm for object-based image coding techniques. This scheme is based on Discrete Wavelet Transform (DWT)/Redundant Discrete Wavelet Transform (RDWT) and Multiresolution Markov Random Field (MMRF). DWT based MMRF works well for noise-free images. It merges details in the original image with their respective visual objects and divides the image into different segments according to their textures. The RDWT based MMRF is a generalization of the DWT based MMRF. When the noise level is high, RDWT based MMRF reduces the influence of noise in the segmentation procedure and generates much better results at some computing costs. The proposed algorithm has been successfully integrated with our DWT based Region of Interest (ROI) compression coder, the Generalized Self-Similarity Trees (GST) codec, for networking applications.

name of conference

  • 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258)

published proceedings

  • ICASSP '99: 1999 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, PROCEEDINGS VOLS I-VI

author list (cited authors)

  • Zheng, L., Liu, J. C., Chan, A. K., & Smith, W.

citation count

  • 6

complete list of authors

  • Zheng, L||Liu, JC||Chan, AK||Smith, W

publication date

  • January 1999