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A general framework for low level vision
Open accessAbstract
We introduce a new geometrical framework based on which natural flows for image scale space and enhancement are presented. We consider intensity images as surfaces in the (x, I) space. The image is, thereby, a two-dimensional (2-D) surface in three-dimensional (3-D) space for gray-level images, and 2-D surfaces in five dimensions for color images. The new formulation unifies many classical schemes and algorithms via a simple scaling of the intensity contrast, and results in new and efficient schemes. Extensions to multidimensional signals become natural and lead to powerful denoising and scale space algorithms.
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Citations
Cited by
chambolle (2004) · doi:10.1023/b:jmiv.0000011321.19549.88 · Cited by 3,227
Image Sharpening by Flows Based on Triple Well Potentials
Gilboa, G., Sochen, N., & Zeevi, Y. Y. (2004) · Journal of Mathematical Imaging and Vision · doi:10.1023/b:jmiv.0000011320.81911.38 · Cited by 616
Self-citationBilateral Filtering: Theory and Applications
Paris, S., Kornprobst, P., Tumblin, J., & Durand, F. (2009) · Foundations and Trends in Computer Graphics and Vision · doi:10.1561/0600000020 · Cited by 586
Adaptive Bilateral Filter for Sharpness Enhancement and Noise Removal
Zhang, B., & Allebach, J. P. (2008) · IEEE Transactions on Image Processing · doi:10.1109/tip.2008.919949 · Cited by 403
Perceptual Metrics for Image Database Navigation
Rubner, Y., & Tomasi, C. (2001) · Springer eBooks · doi:10.1007/978-1-4757-3343-3 · Cited by 296
Metadata
- Authors
- Sochen, N., Kimmel, R., & Malladi, R.
- Venue
- IEEE Transactions on Image Processing
- Published
- 1998-03
- Volume
- 7
- Issue
- 3
- Pages
- 310-318
- ISSN
- 1057-7149 (ISSN-L)
- OpenAlex
- W2104404402
- Cited by
- 615
- References
- 0
- FWCI
- 22.72
- Type
- journal article
- Language
- en
- Open access
- green
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- Sochen, N., Kimmel, R., & Malladi, R. (1998). A general framework for low level vision. IEEE Transactions on Image Processing. https://doi.org/10.1109/83.661181
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