Abstract
Image basis function plays a key role in image information analysis. Due to the complex geometric structure in image, a better image basis or frame often have a very large family with a large number of basis functions lying in a lower dimensionality manifold, such as 2D Gabor functions and Contourlets used in image texture analysis, the corresponding image transform and analysis will be very time consuming. In this article, we propose a novel image representation method called “image elementary manifold”, here, an image elementary manifold can represent all the basis functions lying in the same manifold. A fast elementary manifold based image decomposition and reconstruction algorithm are given. Comparing to traditional image representation methods, elementary manifold based image analysis reduce time consumption, discovers the latent intrinsic structure of images more efficiently and provides the possibility of empirical prediction. Finally, many experiments show the feasibility of image elementary manifold in image analysis.
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Cai, C., Li, L., Zheng, C. (2019). Image Elementary Manifold and Its Application in Image Analysis. In: Sun, F., Liu, H., Hu, D. (eds) Cognitive Systems and Signal Processing. ICCSIP 2018. Communications in Computer and Information Science, vol 1005. Springer, Singapore. https://doi.org/10.1007/978-981-13-7983-3_12
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DOI: https://doi.org/10.1007/978-981-13-7983-3_12
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