Skip to main content

A modified SPIHT algorithm for image coding with a joint MSE and classification distortion measure.

Publication ,  Journal Article
Chang, S; Carin, L
Published in: IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
March 2006

The set partitioning in hierarchical trees (SPIHT) algorithm is an efficient wavelet-based progressive image-compression technique, designed to minimize the mean-squared error (MSE) between the original and decoded imagery. However, the MSE-based distortion measure is not in general well correlated with image-recognition quality, especially at low bit rates. Specifically, low-amplitude wavelet coefficients that may be important for classification are given low priority by conventional SPIHT. In this paper, we use the kernel matching pursuits (KMP) method to autonomously estimate the importance of each wavelet subband for distinguishing between different textures, with textural segmentation first performed via a hidden Markov tree. Based on subband importance determined via KMP, we scale the wavelet coefficients prior to SPIHT coding, with the goal of minimizing a Lagrangian distortion based jointly on the MSE and classification error. For comparison we consider Bayes tree-structured vector quantization (B-TSVQ), also designed to obtain a tradeoff between MSE and classification error. The performances of the original SPIHT, the modified SPIHT, and B-TSVQ are compared.

Duke Scholars

Published In

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

DOI

EISSN

1941-0042

ISSN

1057-7149

Publication Date

March 2006

Volume

15

Issue

3

Start / End Page

713 / 725

Related Subject Headings

  • Signal Processing, Computer-Assisted
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Models, Statistical
  • Markov Chains
  • Least-Squares Analysis
  • Image Interpretation, Computer-Assisted
  • Image Enhancement
  • Data Compression
  • Computer Communication Networks
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Chang, S., & Carin, L. (2006). A modified SPIHT algorithm for image coding with a joint MSE and classification distortion measure. IEEE Transactions on Image Processing : A Publication of the IEEE Signal Processing Society, 15(3), 713–725. https://doi.org/10.1109/tip.2005.860595
Chang, Shaorong, and Lawrence Carin. “A modified SPIHT algorithm for image coding with a joint MSE and classification distortion measure.IEEE Transactions on Image Processing : A Publication of the IEEE Signal Processing Society 15, no. 3 (March 2006): 713–25. https://doi.org/10.1109/tip.2005.860595.
Chang S, Carin L. A modified SPIHT algorithm for image coding with a joint MSE and classification distortion measure. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. 2006 Mar;15(3):713–25.
Chang, Shaorong, and Lawrence Carin. “A modified SPIHT algorithm for image coding with a joint MSE and classification distortion measure.IEEE Transactions on Image Processing : A Publication of the IEEE Signal Processing Society, vol. 15, no. 3, Mar. 2006, pp. 713–25. Epmc, doi:10.1109/tip.2005.860595.
Chang S, Carin L. A modified SPIHT algorithm for image coding with a joint MSE and classification distortion measure. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. 2006 Mar;15(3):713–725.

Published In

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

DOI

EISSN

1941-0042

ISSN

1057-7149

Publication Date

March 2006

Volume

15

Issue

3

Start / End Page

713 / 725

Related Subject Headings

  • Signal Processing, Computer-Assisted
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Models, Statistical
  • Markov Chains
  • Least-Squares Analysis
  • Image Interpretation, Computer-Assisted
  • Image Enhancement
  • Data Compression
  • Computer Communication Networks