Universal Joint Image Clustering and Registration Using Multivariate Information Measures
| Autor: | Lav R. Varshney, Ravi Kiran Raman |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Pixel
Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image registration 020206 networking & telecommunications Pattern recognition 02 engineering and technology Mutual information Image (mathematics) Asymptotically optimal algorithm Computer Science::Computer Vision and Pattern Recognition Signal Processing 0202 electrical engineering electronic engineering information engineering Unsupervised learning 020201 artificial intelligence & image processing Pairwise comparison Artificial intelligence Electrical and Electronic Engineering business Cluster analysis |
| Zdroj: | IEEE Journal of Selected Topics in Signal Processing. 12:928-943 |
| ISSN: | 1941-0484 1932-4553 |
| DOI: | 10.1109/jstsp.2018.2855057 |
| Popis: | We consider the problem of universal joint clustering and registration of images. Image clustering focuses on grouping similar images, while image registration refers to the task of aligning copies of an image that have been subject to rigid-body transformations, such as rotations and translations. We first study registering two images using maximum mutual information and prove its asymptotic optimality. We then show the shortcomings of pairwise registration in multi-image registration, and design an asymptotically optimal algorithm based on multi-information. Further, we define a novel multivariate information functional to perform joint clustering and registration of images, and prove consistency of the algorithm. Finally, we consider registration and clustering of numerous limited-resolution images, defining algorithms that are order-optimal in scaling of number of pixels in each image with the number of images. |
| Databáze: | OpenAIRE |
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