Structured Total Least Squares for Color Image Restoration

Haoying Fu, Michael K. Ng, Jesse L. Barlow

Research output: Contribution to journalJournal articlepeer-review

10 Citations (Scopus)
19 Downloads (Pure)


The problem of 3 x 3 color mixing image restoration is considered. The blurring matrices, as well as the observed image, are contaminated by noise; therefore the total least squares (TLS) method is employed to restore the original image. Since the blurring matrices are also structured, we apply the structured total least squares (STLS) method [J. B. Rosen, H. Park, and J. Glick, SIAM J. Matrix Anal. Appl., 17 (1996), pp. 110-126]. The blurring matrices are generally ill conditioned; thus Tikhonov's regularization is used to stabilize the solution. Since Neumann boundary conditions are used in the restoration process, the discrete cosine transform (DCT) based preconditioner is effective for the linear systems encountered in our STLS algorithm.

Original languageEnglish
Pages (from-to)1100-1119
Number of pages20
JournalSIAM Journal on Scientific Computing
Issue number3
Publication statusPublished - 4 Aug 2006

Scopus Subject Areas

  • Computational Mathematics
  • Applied Mathematics

User-Defined Keywords

  • structured total least squares
  • color image
  • image restoration
  • Toeplitz-like matrices
  • preconditioners


Dive into the research topics of 'Structured Total Least Squares for Color Image Restoration'. Together they form a unique fingerprint.

Cite this