Abstract
In this work we derive a novel density driven diffusion scheme for image enhancement. Our approach, called D3, is a semi-local method that uses an initial structure-preserving oversegmentation step of the input image. Because of this, each segment will approximately conform to a homogeneous region in the image, allowing us to easily estimate parameters of the underlying stochastic process thus achieving adaptive non-linear filtering. Our method is capable of producing competitive results when compared to state-of-the-art methods such as non-local means, BM3D and tensor driven diffusion on both color and grayscale images.
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Åström, F., Zografos, V., Felsberg, M. (2013). Density Driven Diffusion. In: Kämäräinen, JK., Koskela, M. (eds) Image Analysis. SCIA 2013. Lecture Notes in Computer Science, vol 7944. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38886-6_67
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DOI: https://doi.org/10.1007/978-3-642-38886-6_67
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