A new image segmentation algorithm with applications to image inpainting
This article describes a new approach to perform image segmentation. First an image is locally modeled using a spatial autoregressive model for the image intensity. Then the residual autoregressive image is computed. This resulting image possesses interesting texture features. The borders and edges are highlighted, suggesting that our algorithm can be used for border detection. Experimental results with real images are provided to verify how the algorithm works in practice. A robust version of our algorithm is also discussed, to be used when the original image is contaminated with additive outliers. A novel application in the context of image inpainting is also offered.
Year of publication: |
2010
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Authors: | Ojeda, Silvia ; Vallejos, Ronny ; Bustos, Oscar |
Published in: |
Computational Statistics & Data Analysis. - Elsevier, ISSN 0167-9473. - Vol. 54.2010, 9, p. 2082-2093
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Publisher: |
Elsevier |
Keywords: | Image segmentation Border detection Spatial AR models Robust estimators Image inpainting |
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