On prediction of DCT-based denoising efficiency under spatially correlated noise conditions
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
| Original language | English |
|---|---|
| Title of host publication | 2016 13th International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET) |
| Publisher | IEEE |
| Pages | 750-754 |
| Number of pages | 5 |
| ISBN (Print) | 9786176078067 |
| DOIs | |
| Publication status | Published - 12 Apr 2016 |
| Publication type | A4 Article in a conference publication |
| Event | International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science - Duration: 1 Jan 2000 → … |
Conference
| Conference | International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science |
|---|---|
| Period | 1/01/00 → … |
Abstract
In this paper, results of image denoising efficiency prediction for filter based on discrete cosine transform (DCT) for the case of spatially correlated additive Gaussian Noise (SCGN) are given. The considered noise model is analyzed for different degrees of spatial correlation that produce varying non-homogeneous spectrum of the noise. PSNR metric is exploited to assess denoising efficiency. It is shown in this paper, that a prediction of denoising efficiency has high accuracy for data distorted by noise with different degrees of spatial correlation, and require low computational resources.
ASJC Scopus subject areas
Keywords
- Denoising, Efficiency Prediction, Fitting, Spatially Correlated Noise