An adaptive constrained least square approach for removing blocking effect

S.W. Hong, Yuk Hee Chan, W.C. Siu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic research


This paper presents a new adaptive objective function based on the regularized iterative block reduction technique for low-bit rate transform coded images. Also, a better initial estimate for the regularization approach is presented. Two types of prior knowledge are used: the first type bounds the maximum tolerable error (roughness), and the second type restricts the high-frequency content (smoothness) of the restored images. Computer simulations showed that the new adaptive objective function with the proposed initial estimate performed better on both subjective and objective measures than did a previously proposed objective function.
Original languageEnglish
Title of host publication[Missing Source Name from PIRA]
ISBN (Print)0780321278
Publication statusPublished - 1995


  • Computational complexity
  • Computer simulation
  • Constraint theory
  • Estimation
  • Functions
  • Image compression
  • Image reconstruction
  • Least squares approximations


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