Publications by Sabine Süsstrunk

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Image noise can often be accurately fitted to a Poisson-Gaussian distribution. However, estimating the distribution parameters from a noisy image only is a challenging task. Here, we study the case when paired noisy and noise-free samples are accessible. N ...

The accurate measurement of reflectance and transmittance properties of materials is essential in the printing and display industries in order to ensure precise color reproduction. In comparison with reflectance measurement, where the impact of different g ...

Recently, we have proposed a new image device called gigavision camera whose most important characteristic is that pixels have binary response. The response function of a gigavision sensor is non-linear and similar to a logarithmic function, which makes the camera suitable for high dynamic range imaging. One important parameter in the gigavision camera is the threshold for generating binary pixels. Threshold T relates to the number of photo-electrons necessary for the pixel output to switch from "0" to "1".

Joint processing of visible (RGB) and near-infrared (NIR) images has recently found some appealing applications, which make joint capturing a pair of visible and NIR images an important problem. In this paper, we propose a new method to design color filter ...

We propose using a single silicon sensor and a modified Bayer CFA for joint acquisition of color and near-infrared (NIR) images. Silicon sensors, which are placed in most color cameras, are inherently sensitive to NIR. Hence, our proposed design is very similar to consumer color cameras in terms of hardware. The main contribution of this work is an algorithm that estimates full-resolution color and NIR images from subsampled and mixed sensor measurements. Our method results in high-quality RGB and NIR image

Assuming that the photoreceptor response of the human visual system is adaptive and non-linear, we can derive mathematical properties that can account for both color discrimination and chromatic adaptation. This could be due to the photoreceptors’ response to illumination, which is non-linear and varies according to the adaptation state. Assuming the Naka-Rushton nonlinear function and an automatic gain control function, we can derive color discrimination and chromatic adaptation data. We extend the discus

We propose a method for accurate and temporally consistent surface classification in the presence of noisy, irregularly sampled measurements, and apply it to the estimation of snow coverage over time. The input imagery is extremely challenging, with large ...

We present a study of radiometric calibration and the in-camera imaging process through an extensive analysis of more than 10,000 images from over 30 cameras. The goal is to investigate if image values can be transformed to physically meaningful values and ...

Color image quality depends on many factors, such as the initial capture system and its color image processing, compression, transmission, the output device, media and associated viewing conditions. In this paper, we are primarily concerned with color image quality in relation to compression and transmission. We review the typical visual artifacts that occur due to high compression ratios and/or transmission errors. We discuss color image quality metrics and present no-reference artifact metrics for blockin

In the evolving landscape of deep learning, there is a pressing need for more comprehensive datasets capable of training models across multiple modalities. Concurrently, in digital humanities, there is a growing demand to leverage technology for diverse media adaptation and creation, yet limited by sparse datasets due to copyright and stylistic constraints. Addressing this gap, our paper presents a novel dataset comprising Franco-Belgian comics from the 1950s annotated for tasks including depth estimation,

The performance of many color science and imaging algorithms are evaluated based on their mean errors. However, if these errors are not normally distributed, statistical evaluations based on the mean are not appropriate performance metrics. We present a no ...

"Pictures of objects behind a glass are difficult to interpret" "and understand due to the superposition of two real images: a reflection layer and a background layer. Separation of these two layers is challenging due to the ambiguities in as- signing text ...

We present an algorithm for clustering sets of detected interest points into groups that correspond to visually distinct structure. Through the use of a suitable colour and texture representation, our clustering method is able to identify keypoints that be ...

Recently we have proposed a new image device called the gigavision camera. The main feature of this camera is that the pixels have a binary response. The response function of a gigavision sensor is non-linear and similar to a logarithmic function, which ma ...

We present a statistical framework to automatically determine an associated color for a given arbitrary semantic expression. The expression can not only be a color name but any word or character string. In addition to the color value, we are also able to c ...

Recent advances have shown the great power of deep convolutional neural networks (CNN) to learn the relationship between low and high-resolution image patches. However, these methods only take a single-scale image as input and require large amount of data ...

A camera for simultaneously capturing a visible and near-infrared (NIR) image of one or more objects, the camera comprising: at least one colour filter array (CFA) including at least four different filters, said at least one colour filter array having visi ...

Classic image-restoration algorithms use a variety of priors, either implicitly or explicitly. Their priors are hand-designed and their corresponding weights are heuristically assigned. Hence, deep learning methods often produce superior image restoration ...

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 ...

Silicon-based digital camera sensors exhibit significant sensitivity beyond the visible spectrum (400-700nm). They are able to capture wavelengths up to 1100 nm, i.e., they are sensitive to near-infrared (NIR) radiation. This additional information is conventionally treated as noise and is absorbed by a NIR-blocking filter affixed to the sensor. We show that retaining instead of removing NIR information can significantly improve certain computational photography and computer vision tasks. Indeed, intrinsic

Sabine Süsstrunk

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PoGaIN: Poisson-Gaussian Image Noise Modeling From Paired Samples

Comparative analysis of transmittance measurement geometries and apparatus

On Pixel Detection Threshold in the Gigavision Camera

Correlation-based Joint Acquisition and Demosaicing of Visible and Near-Infrared Images

Compressive Acquisition of Color and Near-Infrared Images

On Adaptive Non-Linarity for Color Discrimination and Chromatic Adaptation

Temporally Consistent Snow Cover Estimation from Noisy, Irregularly Sampled Measurements

Revisiting Radiometric Calibration for Color Computer Vision

Color image quality on the Internet

Unlocking Comics: the Ai4va Dataset for Visual Understanding

Evaluating Chromatic Adaptation Transform Performance

Learning to See through Reflections

Appearance-based Keypoint Clustering

Image Reconstruction in the Gigavision Camera

What is the color of chocolate? - extracting color values of semantic expressions

Multi-Modal Spectral Image Super-Resolution

Camera design for the simultaneous capture of near-infrared and visible images

BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image Restoration

Linear demosaicing inspired by the human visual system

Enhancing the Visible with the Invisible: Exploiting Near-Infrared to Advance Computational Photography and Computer Vision