145 citations · 186 across the 6 of their papers we have counts for
6 papers
A Bimodal Co-Sparse Analysis Model for Image Processing
Martin Kiechle, Tim Habigt, Simon Hawe +1
The success of many computer vision tasks lies in the ability to exploit the interdependency between different image modalities such as intensity and depth. Fusing corresponding in…
Co-Sparse Textural Similarity for Image Segmentation
Claudia Nieuwenhuis, Daniel Cremers, Simon Hawe +1
We propose an algorithm for segmenting natural images based on texture and color information, which leverages the co-sparse analysis model for image segmentation within a convex mu…
A Joint Intensity and Depth Co-Sparse Analysis Model for Depth Map Super-Resolution
Martin Kiechle, Simon Hawe, Martin Kleinsteuber
High-resolution depth maps can be inferred from low-resolution depth measurements and an additional high-resolution intensity image of the same scene. To that end, we introduce a b…
Analysis Based Blind Compressive Sensing
Julian Wörmann, Simon Hawe, Martin Kleinsteuber
In this work we address the problem of blindly reconstructing compressively sensed signals by exploiting the co-sparse analysis model. In the analysis model it is assumed that a si…
Separable Dictionary Learning
Simon Hawe, Matthias Seibert, Martin Kleinsteuber
Many techniques in computer vision, machine learning, and statistics rely on the fact that a signal of interest admits a sparse representation over some dictionary. Dictionaries ar…
Analysis Operator Learning and Its Application to Image Reconstruction
Simon Hawe, Martin Kleinsteuber, Klaus Diepold
Exploiting a priori known structural information lies at the core of many image reconstruction methods that can be stated as inverse problems. The synthesis model, which assumes th…