Chair of
Multimedia Communications and Signal Processing
Prof. Dr.-Ing. André Kaup
The content of the English page is outdated, please use the updated German version of our page at the moment:

Image Reconstruction from Arbitrary Pixel Meshes

Field of activity: Video Signal Processing and Transmission
Research topic: Video Analysis and Video Processing

Digital images are commonly represented as regular 2D arrays, so pixels are organized in form of a matrix addressed by integers. However, there are many image processing operations, such as rotation or motion compensation, that produce pixels at non-integer positions. These pixels have to be resampled onto the regular grid so the resulting image can be stored, displayed or further processed. This resampling can be alternatively seen as a reconstruction problem where the unknown pixels on the regular grid are recovered using the available samples at non-integer positions. Typically, existing image reconstruction techniques cannot handle samples at non-integer positions. This research focuses on developing a new technique that yields high quality reconstructions. These can be later employed for different purposes, ranging from super-resolution and refocusing to video coding and warping.

The following video offers a brief demonstration of how pixels located at non-integer positions affect the visual quality.


J. Koloda, J. Seiler, A. Kaup

Reliability-based Mesh-to-Grid Image Reconstruction
accepted for IEEE Workshop on Multimedia Signal Processing (MMSP), Montreal, Canada, Sep. 2016
J. Koloda, J. Seiler, A.M. Peinado, A. Kaup

Multi-mode kernel-based minimum mean square error estimator for accelerated image error concealment
accepted for Data Compression Conference (DCC), Snowbird (Utah), USA, Mar. 2016
J. Koloda, J. Seiler, A. Kaup

Denoising-based image reconstruction from pixels located at non-integer positions
IEEE Int. Conf. on Image Processing (ICIP), Pages: 4565 - 4569, Québec City, Canada, Sep. 2015