Proceedings. International Conference on Information Technology: Coding and Computing
DOI: 10.1109/itcc.2002.1000370
|View full text |Cite
|
Sign up to set email alerts
|

On a certain class of algorithms for noise removal in image processing: a comparative study

Abstract: The effectiveness of restoration techniques mainly depends on the accuracy of the image modeling. One of the most popular degradation models is based on the assumption that the image blur can be modeled as a superposition with an impulse response H that may be space variant and its output is subject to an additive noise. Our research aimed the use of statistical concepts and tools for developing a new class of image restoration algorithms. Several variants of a heuristic scatter matrices based algorithm (HSBA)… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
3
0

Publication Types

Select...
2
1
1

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(3 citation statements)
references
References 9 publications
0
3
0
Order By: Relevance
“…Basically, the AMVR algorithm works in two stages, namely the removal of the mean component of the noise (Step 1 and Step 2), and the decrease of the variance of the noise using the adaptive filter MMSE. The description of the AMVR algorithm is (Cocianu, State & Vlamos, 2002) Step 2. Compute X , the sample mean estimate of the initial image X, by averaging the…”
Section: Minimum Mean-square Error Filtering (Mmse) and The Adaptivementioning
confidence: 99%
See 1 more Smart Citation
“…Basically, the AMVR algorithm works in two stages, namely the removal of the mean component of the noise (Step 1 and Step 2), and the decrease of the variance of the noise using the adaptive filter MMSE. The description of the AMVR algorithm is (Cocianu, State & Vlamos, 2002) Step 2. Compute X , the sample mean estimate of the initial image X, by averaging the…”
Section: Minimum Mean-square Error Filtering (Mmse) and The Adaptivementioning
confidence: 99%
“…In other words, the effects determined by the application of mean filters are merely the decrease of the local variance corresponding to each processed window, and consequently to inhibit the variance component of the noise. The AMVR algorithm (Adaptive Mean Variance Removal) allows the removal of the normal/uniform noise whatever the mean of the noise is (Cocianu, State, & Vlamos, 2002). Similar to MMSE (Minimum Mean Square Error) filtering technique (Umbaugh, 1998) the application of the AMVR algorithm requires that the noise parameters and some additional features are known.…”
Section: Introductionmentioning
confidence: 99%
“…Because of this, the noise removal procedure is one of the most commonly used pre-processing step in solving digital image processing tasks. Therefore, a significant part of digital image procedures are dedicated to image denoising, most of them being developed under the assumptions that the images are corrupted by additive white noise [1], [2], [3], [4]. In our work, we keep the assumption about normality, but we consider that the superimposed noise affects neighbour image pixels in a correlated manner.…”
Section: Introductionmentioning
confidence: 99%