Medical image mosaic based on low-overlapping regions
| Autor: | Mei Zhou, Feng Zhang, Hongying Liu, Chen Xuerong, Qingli Li |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Image fusion
Matching (graph theory) Computer science business.industry Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 0211 other engineering and technologies Image registration Pattern recognition 02 engineering and technology Composite image filter Image (mathematics) Feature (computer vision) Robustness (computer science) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business 021101 geological & geomatics engineering |
| Zdroj: | CISP-BMEI |
| Popis: | This paper focuses on the mosaicing of microscopic medical images. Different from regular application scene where the source images usually have an overlapping ratio between 30%∼50%, source images in this paper have a rather low overlapping ratio less than 15%. Performances of several generic feature-based registration methods are compared in order to explore which one is most appropriate for our application. This paper presents a novel mosaic algorithm as follows. Firstly, Speeded-up Robust Feature (SURF) points in the regions surrounding the overlapped are extracted and then roughly matching results of feature points are acquired. Secondly, mismatched pairs are eliminated according to spatial distance of matching points, and then geometrical relationship between reference image and target image is determined. Finally, registered images are blended into a composite image with modified weighted smooth algorithm. Experimental results demonstrate that the proposed method is effective to create a visually pleasant panoramic image. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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