This is a selection of the major projects. A complete list of publications can be found here.

The new per-pixel image quality dataset with computer graphics artifacts shows disapointing performance of both simple (PSNR, MSE, sCIE-Lab) and advanced (SSIM, MS-SSIM, HDR-VDP-2) quality metrics.
Unlike standard LCD or Plasma displays, a high dynamic range (HDR) display is capable of showing images of very high contrast (up to 250,000:1) and peak brightness (up to 2,400 cd/m^2). As a result, the images and video shown on such as display look very realistic and appealing.

A metric for predicting visible differences (discrimination) and image quality (mean-opinion-score) in high dynamic range images. The metric is carefully calibrated and extensively tested against actual experimental data, ensuring the highest possible accuracy.

HDR images are captured in a single exposure with standard cameras by encoding information about the saturated pixels in a glare. The glare is produced by a cross-screen (star) filter, making it amenable to tomographic reconstruction.

Digital viewfinder in cameras does not show depth-of-field, lack of sharpness or motion blur, which is normally visible in a full-size image. Based on blur-matching experimental data, the algorithm produces lower resolution images while preserving apperent blur.

A method for displaying HDR images with exposure control in a web browser. The project page includes a toolkit for generating web pages with HDR images.

Color distortions due to tone-mapping are corrected by adjusting image color saturation. A model of color adjustment is built based on the data from an appearance-matching experiment.

A tone-mapping algorithm that is controlled by a super-threshold visual metric. The solution takes into account display limitations, such as brightness, black level, and reflected ambient light.

A visual metric that is mostly invariant to contrast and tone-scale manipulations. It can detect loss of visible contrast, amplification of invisible contrast and contrast reversal.

A semi-automatic method for classification of reflective and emissive objects in video, followed by brightness enhancement for display on high dynamic range displays.

A generic model of a local tone-mapping operator is fit to a pair of LDR and HDR images. The model is applied for backward compatible HDR image compression, analysis of tone-mapping operators and synthesis of new operators from existing ones.

The perceived brightness of the glare illusion is measured in a brightness matching experiment. A simple Gaussian convolution is shown to produce similar brightness boost as a physically correct PSF model of the eye optics.
For older projects visit the MPI HDR Projects web page or go to the publication list and click on the 'project page' link.