Publications by Sabine Süsstrunk

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We present a method for retrieving illuminant spectra from a set of images taken with a fixed location camera, such as a surveillance or panoramic one. In these images, there will be significant changes in lighting conditions and scene content, but there will also be static elements in the background. As color constancy is an under-determined problem, we propose to exploit the redundancy and constancy offered by the static image elements to reduce the dimensionality of the problem. Specifically, we assume t

Salient object detection is evaluated using binary ground truth (GT) with the labels being salient object class and background. In this study, the authors corroborate based on three subjective experiments on a novel image dataset that objects in natural im ...

Texture modeling and synthesis are essential for enhancing the realism of virtual environments. Methods that directly synthesize textures in 3D offer distinct advantages to the UV-mapping-based methods as they can create seamless textures and align more cl ...

Neural Cellular Automata (NCA) is a class of Cellular Automata where the update rule is parameterized by a neural network that can be trained using gradient descent. In this paper, we focus on NCA models used for texture synthesis, where the update rule is ...

Skin tones, portraits in particular, are of critical importance in photography and video, but a number of factors, such as pigmentation irregularities (e.g., moles, freckles), irritation, roughness, or wrinkles can reduce their appeal. Moreover, such “defe ...

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

We address the problem of re-rendering images to high dynamic range (HDR) displays, which were originally tone-mapped to standard displays. As these new HDR displays have a much larger dynamic range than standard displays, an image rendered to standard mon ...

Low-light photography produces images with low signal-to-noise ratios due to limited photons. In such conditions, common approximations like the Gaussian noise model fall short, and many denoising techniques fail to remove noise effectively. Although deep- ...

Neural cellular automata (NCA) are a class of cellular automata where the update rule is parameterized by a neural network that can be trained using gradient descent. In this article, we focus on NCA models used for texture synthesis, where the update rule is inspired by partial differential equations (PDEs) describing reaction-diffusion systems. To train the NCA model, the spatiotemporal domain is discretized, and Euler integration is used to numerically simulate the dynamics. Crucially, it is unclear whet

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 a

We present a tone mapping algorithm that is derived from a model of retinal processing. Our approach has two major improvements over existing methods. First, tone mapping is applied directly on the mosaic image captured by the sensor, analogue to the human ...

Digital camera sensors are sensitive to wavelengths ranging from the ultraviolet (200-400nm) to the near-infrared (700-100nm) bands. This range is, however, reduced because the aim of photographic cameras is to capture and reproduce the visible spectrum (4 ...

Sensors of most digital cameras are made of silicon that is inherently sensitive to both the visible and near-infrared parts of the electromagnetic spectrum. In this paper, we address the problem of color and NIR joint acquisition. We propose a framework f ...

Videos representing flames, water, smoke, etc. are often defined as dynamic textures: "textures" because they are characterized by redundant repetition of a pattern and "dynamic" because this repetition is also in time and not only in space. Dynamic textur ...

Diffusion models are usually trained using isotropic noise. Yet, common data distributions are strongly anisotropic. We explain that this covariance mismatch negatively impacts the model in several ways. It leads to the model predicting only the high-variance components at high noise levels and only the low-variance components at low noise levels, requiring a wide range of noise levels during training and inference to model all components accurately. This partition of components across noise levels also pre

Deep neural networks for semantic segmentation are most often trained with RGB color images, which encode the radiation visible to the human eyes. In this paper, we study if additional physical scene information, specifically Near-Infrared (NIR) images, im ...

Color images acquired through single chip digital cameras using a color filter array (CFA) contain a mixture of luminance and opponent chromatic information that share their representation in the spatial Fourier spectrum. This mixture could result in aliasing if the bandwidths of these signals are too wide and their spectra overlap. In such a case, reconstructing three-color per pixel images without error is impossible. One way to improve the reconstruction is to have sensitivity functions that are highly c

Chromatic aberration, caused by photographic lens imperfections, results in the image of only one spectral channel being sharp, while the other channels are blurred depending on their wavelengths difference with the sharp channel. We study chromatic aberra ...

In this paper, we develop a MultiTask Learning (MTL) model to achieve dense predictions for comic panels to, in turn, facilitate the transfer of comics from one publication channel to another by assisting authors in the task of reconfiguring their narrativ ...

In landscape photography, distant objects often appear blurred with a blue color cast, a degradation caused by atmospheric haze. To enhance image contrast, pleasantness and information content, dehazing can be performed. We propose that fusing a visible an ...

Sabine Süsstrunk

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Daylight illuminant retrieval using redundant image elements

Evaluating salient object detection in natural images with multiple objects having multi-level saliency

Mesh Neural Cellular Automata

NoiseNCA: Noisy Seed Improves Spatio-Temporal Continuity of Neural Cellular Automata

Automatic Skin Enhancement with Visible and Near-Infrared Image Fusion

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Tone Mapping For High Dynamic Range Displays

Dark Noise Diffusion: Noise Synthesis for Low-Light Image Denoising

Discovering Partial Differential Equations With Neural Cellular Automata

Chromatic contrast detection in spatial chromatic noise

A Model of Retinal Local Adaptation for the Tone Mapping of Color Filter Array Images

Illuminant estimation and detection using near infrared

A Novel Compressive Sensing Approach to Simultaneously Acquire Color and Near-infrared Images on a Single Sensor

Higher Order SVD Analysis for Dynamic Texture Synthesis

Covariance Mismatch in Diffusion Models

Deep Semantic Segmentation Using Nir As Extra Physical Information

Influence of Spectral Sensitivity Functions on color demosaicing

Multiscale guided deblurring: Chromatic aberration correction in color and near-infrared imaging

Dense Multitask Learning to Reconfigure Comics

Color Image Dehazing using the Near-Infrared