The richness of natural images makes the quest for optimal representations in image
processing and computer vision challenging. The latter observation has not prevented the …

Improving the modeling of natural images is important to go beyond the state-of-the-art for
many image processing tasks such as compression, denoising, inverse problems, and …

Compression is an important field of digital image processing where well-engineered
methods with high performance exist. Partial differential equations (PDEs), however, have …

Galić et al.(Journal of Mathematical Imaging and Vision 31: 255–269, 2008) have shown
that compression based on edge-enhancing anisotropic diffusion (EED) can outperform the …

While methods based on partial differential equations (PDEs) and variational techniques are
powerful tools for denoising and inpainting digital images, their use for image compression …

We introduce and discuss shape-based models for finding the best interpolation data when
reconstructing missing regions in images by means of solving the Laplace equation. The …

Harmonic inpainting with optimised data is very popular for inpainting-based image
compression. We improve this approach in three important aspects. Firstly, we replace the …

Diffusion-based inpainting can reconstruct missing image areas with high quality from
sparse data, provided that their location and their values are well optimised. This is …

The use of image and video communication has increased dramatically in recent years.
When it is necessary to securely transmit data in limited bandwidth, both compression and …

Although widely used standards such as JPEG and JPEG 2000 exist in the literature, lossy
image compression is still a subject of ongoing research. Galić et al.(2008) have shown that …