A block-based noise level estimation from X-ray images in SVD domain
| Autor: | Alen Begovic, Emir Turajlic, Namir Skaljo |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Noise measurement
Segmentation-based object categorization business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-space segmentation Image processing Pattern recognition 02 engineering and technology Image segmentation 030218 nuclear medicine & medical imaging 03 medical and health sciences Noise 0302 clinical medicine Image texture Computer Science::Computer Vision and Pattern Recognition 0202 electrical engineering electronic engineering information engineering Image noise 020201 artificial intelligence & image processing Computer vision Artificial intelligence business |
| Zdroj: | IWSSIP |
| DOI: | 10.1109/iwssip.2017.7965569 |
| Popis: | Accurate and fast estimation of noise levels from medical images has numerous applications in medical image processing, including image enhancement, image segmentation and feature extraction. In this paper, a block-based noise level estimation algorithm in SVD domain is proposed. The proposed algorithm employs the non-overlapping block image segmentation to estimate homogenous image regions. Each homogenous block is used to obtain an independent noise level estimates in SVD domain. For any particular image, the overall noise level estimate is ascertained by averaging over the set of noise level estimates associated with the homogenous image blocks. In this paper, the optimal size of image segmentation blocks is evaluated systematically over a large dataset of x-ray images. The experimental results show that the proposed method offers numerous advantages over some alternative SVD domain method. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|