Total variation-based image noise reduction with generalized fidelity function

Suk Ho Lee, Moon Gi Kang

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


In this letter, we analyze the relationship between the change in the intensity value and the scale of an image feature, when a generalized function is used as the fidelity term in the total variation-based noise removal scheme. Based on the analysis, we propose a designing method of the fidelity function that results in any desired monotonic relationship between the intensity change and the scale. As an example, we designed a fidelity function that results in a larger contrast between the intensity change of a small scaled feature and that of a large scaled one than the original total variation-based noise removal scheme that uses the L2 norm as the fidelity function.

Original languageEnglish
Pages (from-to)832-835
Number of pages4
JournalIEEE Signal Processing Letters
Issue number11
Publication statusPublished - 2007 Nov

Bibliographical note

Funding Information:
Manuscript received December 29, 2006; revised May 9, 2007. This work was supported in part by the Korea Science and Engineering Foundation (KOSEF) through the Biometrics Engineering Research Center (BERC) and in part by the Seoul Future Contents Convergence (SFCC) Cluster established by the Seoul Industry-Academy-Research Cooperation Project at Yonsei University. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Vince D. Calhoun.

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics


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