Higher order PDE based model for segmenting noisy image
| Autor: | Abdul Halim, Rowthu Vijayakrishna, B. V. Rathish Kumar |
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| Rok vydání: | 2020 |
| Předmět: |
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Unsupervised segmentation Image (mathematics) QA76.75-76.765 Market segmentation Photography Computer software Electrical and Electronic Engineering Image denoising TR1-1050 Partial differential equation business.industry Pattern recognition Image segmentation Fourier spectral method Order (business) Computer Science::Computer Vision and Pattern Recognition Signal Processing unsupervised segmentation Unsupervised learning noisy greyscale image segmentation Computer Vision and Pattern Recognition Artificial intelligence nonlinear PDE model business Software fourth‐order non‐linear partial differential equation |
| Zdroj: | IET Image Processing, Vol 14, Iss 11, Pp 2597-2609 (2020) |
| ISSN: | 1751-9667 1751-9659 |
| DOI: | 10.1049/iet-ipr.2019.0885 |
| Popis: | In this study, a fourth‐order non‐linear partial differential equation (PDE) model together with multi‐well potential has been proposed for greyscale image segmentation. The multi‐well potential is constructed from the histogram of the given image to make the segmentation process fully automatic and unsupervised. Further, the model is refined for effective segmentation of noisy greyscale image. The fourth‐order anisotropic term with the multi‐well potential is shown to properly segment noisy images. Fourier spectral method in space with semi‐implicit convexity splitting in time is used to derive an unconditionally stable scheme. Numerical studies on some standard test images and comparison of results with those in literature clearly depict the superiority of the anisotropic variant of the non‐linear PDE model. |
| Databáze: | OpenAIRE |
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