Image Compression with Anisotropic Diffusion
Journal of Mathematical Imaging and Vision
An integrated method for satellite image interpolation
International Journal of Remote Sensing
Image Magnification by a Compact Method with Preservation of Preferential Components
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Spatial colour gamut mapping by means of anisotropic diffusion
CCIW'11 Proceedings of the Third international conference on Computational color imaging
Image super-resolution by curve fitting in the threshold decomposition domain
Journal of Visual Communication and Image Representation
Super-resolution of single text image by sparse representation
Proceeding of the workshop on Document Analysis and Recognition
Anisotropic Probabilistic Neural Network for Image Interpolation
Journal of Mathematical Imaging and Vision
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To enlarge a digital image from a single frame preserving the perceptive cues is a relevant research issue. The best known algorithms take into account the presence of edges in the luminance channel, to interpolate correctly the samples/pixels of the original image. This approach allows the production of pictures where the interpolated artifacts (aliasing blurring effect, 驴) are limited but where high frequencies are not properly preserved. The zooming algorithm proposed in this paper on the other hand reduces the noise and enhance the contrast to the borders/edges of the enlarged picture using classical anisotropic diffusion improved by a smart heuristic strategy. The method requires limited computational resources and it works on graylevel images, RGB color pictures and Bayer data. Our experiments show that this algorithm outperforms in quality and efficiency the classical interpolation methods (replication, bilinear, bicubic).