Biomedical subjects

Sabine Süsstrunk

Publications and source records attributed to Sabine Süsstrunk.

5 recordsLinked to original sources

PubMed2006

High dynamic range image rendering with a Retinex-based adaptive filter.

We propose a new method to render high dynamic range images that models global and local adaptation of the human visual system. Our method is based on the center-surround Retinex model. The novelties of our method is first to use an adaptive filter, whose shape follows the image high-contrast edges, thus reducing halo artifacts common to other methods. Second, only the luminance channel is processed, which is defined by the first component of a principal component analysis. Principal component analysis provides orthogonality between channels and thus reduces the chromatic changes caused by the modification of luminance. We show that our method efficiently renders high dynamic range images and we compare our results with the current state of the art.

Algorithms↗

PubMed2005

Linear demosaicing inspired by the human visual system.

There is an analogy between single-chip color cameras and the human visual system in that these two systems acquire only one limited wavelength sensitivity band per spatial location. We have exploited this analogy, defining a model that characterizes a one-color per spatial position image as a coding into luminance and chrominance of the corresponding three colors per spatial position image. Luminance is defined with full spatial resolution while chrominance contains subsampled opponent colors. Moreover, luminance and chrominance follow a particular arrangement in the Fourier domain, allowing for demosaicing by spatial frequency filtering. This model shows that visual artifacts after demosaicing are due to aliasing between luminance and chrominance and could be solved using a preprocessing filter. This approach also gives new insights for the representation of single-color per spatial location images and enables formal and controllable procedures to design demosaicing algorithms that perform well compared to concurrent approaches, as demonstrated by experiments.

Algorithms↗

PubMed2004

Eigenregions for image classification.

For certain databases and classification tasks, analyzing images based region features instead of image features results in more accurate classifications. We introduce eigenregions, which are geometrical features that encompass area, location, and shape properties of an image region, even if the region is spatially incoherent. Eigenregions are calculated using principal component analysis (PCA). On a database of 77,000 different regions obtained through the segmentation of 13,500 real-scene photographic images taken by nonprofessionals, eigenregions improved the detection of localized image classes by a noticeable amount. Additionally, eigenregions allow us to prove that the largest variance in natural image region geometry is due to its area and not to shape or position.

Journal Article↗

PubMedDate not supplied

Chromatic contrast detection in spatial chromatic noise.

The spectral properties of chromatic-detection mechanisms were investigated using a noise-masking paradigm. Contrast-detection thresholds were measured for a signal with a Gaussian spatial profile, modulated in the equiluminant plane in the presence of spatial chromatic noise. The noise was distributed within a sector in the equiluminant plane, centered on the signal direction. Each stimulus consisted of two adjacent fields, one of which contained the signal, separated horizontally by a gap with the same average chromaticity as the uniform background. Observers were asked to judge on which side of the central fixation point the signal was displayed via a two-alternative, forced-choice (2AFC) paradigm. Contrast thresholds were measured for four color directions and three sector widths at increasing levels of the average energy of the axial component of the noise. Results show that contrast thresholds are unaffected by the width of the noise sector, as previously found for temporally modulated stimuli (D'Zmura & Knoblauch, 1998). The results are consistent with the existence of spectrally broadband linear-detection mechanisms tuned to the signal color direction and support the hypothesis of the existence of higher-order color mechanisms with sensitivities tuned to intermediate directions in color space.

Acoustic Stimulation↗

PubMedDate not supplied

Effects of motion and configural complexity on color transparency perception.

We tested whether motion and configural complexity affect perceived transparency. A series of five coherent chromatic transformations in color space was applied across a figure: translation, convergence, shear, divergence and rotation. The stimuli consisted of a bipartite or a checkerboard configuration (10 x 10 degrees), with a central static or moving overlay (5 x 5 degrees). Three different luminance conditions (the plane of chromatic transformation oriented toward higher, lower, or equal luminances) were also tested for each of three modulation depths. For each stimulus, the observer judged whether the overlay appeared transparent or not. The main results indicated an interaction between the type of chromatic transformation and stimulus motion and complexity. For example, convergences are judged to appear transparent significantly more often when motion is added for bipartite configurations, or when they are generated in a checkerboard configuration. Surprisingly, shears that have been reported to appear opaque, are more frequently reported to appear transparent with short vector lengths and when combined with motion. Other transformations are also affected by motion, although the effectiveness of figural complexity on transparency seems to depend on both the type of color shifts and the presence of motion. The results indicate that adding motion and stimulus complexity are not necessarily neutral with respect to the chromatic shifts evoking transparency. Thus, studies that have used motion to enhance transparency may yield different results about the color shifts supporting transparency perception from those that did not. The same might be supposed for stimulus complexity under some conditions.

Color Perception↗