JOURNAL ARTICLE

Compact rotation invariant descriptor for non-local means

Nicholas DowsonOlivier Salvado

Year: 2010 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 7623 Pages: 76233C-76233C   Publisher: SPIE

Abstract

Non-local means is a recently proposed denoising technique that better preserves image structures than other methods. However, the computational cost of non-local means is prohibitive, especially for large 3D images. Modifications have previously been proposed to reduce the cost, which result in image artefacts. This paper proposes a compact rotation invariant descriptor. Testing demonstrates improved denoising performance relative to optimized non-local means. Rotation invariant non-local means is an order of magnitude faster.

Keywords:
Computer science Invariant (physics) Rotation (mathematics) Artificial intelligence Computer vision Physics

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Topics

Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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