Abstract
Preconditioned conjugate gradient method is applied for solving linear systemsAx=b where the matrixA is the discretization matrix of second-order elliptic operators. In this paper, we consider the construction of the trnasform based preconditioner from the viewpoint of image compression. Given a smooth image, a major portion of the energy is concentrated in the low frequency regions after image transformation. We can view the matrixA as an image and construct the transform based preconditioner by using the low frequency components of the transformed matrix. It is our hope that the smooth coefficients of the given elliptic operator can be approximated well by the low-rank matrix. Numerical results are reported to show the effectiveness of the preconditioning strategy. Some theoretical results about the properties of our proposed preconditioners and the condition number of the preconditioned matrices are discussed.
| Original language | English |
|---|---|
| Pages (from-to) | 885-900 |
| Number of pages | 16 |
| Journal | BIT Numerical Mathematics |
| Volume | 38 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Dec 1997 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
User-Defined Keywords
- Transform approximation
- Image compression
- Preconditioned conjugate gradient method
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