The Beltrami framework is a successful technique for color image denosing by regarding
color images as manifolds embedded in a five dimensional spatial-chromatic space. It can …

In image processing, the regularization term is always hard to choose. In this paper, we
introduce a model based on the fractional derivative, which is derived from the classical …

The curvature regularities are well-known for providing strong priors in the continuity of
edges, which have been applied to a wide range of applications in image processing and …

The choice of a proper regularization measure plays an important role in the field of image
processing. One classical approach treats color images as two-dimensional surfaces …

Models related to the Euler's elastica energy have proven to be useful for many applications
including image processing. Extending elastica models to color images and multichannel …

Depth from Defocus (DFD) suggests a simple optical set-up to recover the shape of a scene
through imaging with shallow depth of field. Although numerous methods have been …

Reflector-normal angles and reflector-curvature parameters are the principal geometric
attributes used in seismic interpretation for characterizing the orientations and shapes …

We consider the linear and non-linear enhancement of diffusion weighted magnetic
resonance images (DW-MRI) to use contextual information in denoising and inferring fiber …

We propose an effective physical model based single-image dehazing algorithm under the
regularization framework. Using an anisotropic Laplacian term as a constraint, the …

We consider left-invariant diffusion processes on DTI data by embedding the data into the
space R^3\rtimesS^2 of 3D positions and orientations. We then define and solve the …