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Related publications (30)

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A Performance Evaluation of Local Features for Image-Based 3D Reconstruction

Pascal Fua, Bin Fan

This paper performs a comprehensive and comparative evaluation of the state of the art local features for the task of image based 3D reconstruction. The evaluated local features cover the recently developed ones by using powerful machine learning technique ...

2019

Synthetic electronic video containing a hidden image

Sabine Süsstrunk, Roger Hersch, Mahmut Sami Arpa

We present a method for hiding images in synthetic videos and reveal them by temporal averaging. We developed a visual masking method that hides the input image both spatially and temporally. Our masking approach consists of temporal and spatial pixel by p ...

2019

Biomedical Image Reconstruction: From the Foundations to Deep Neural Networks

Michaël Unser, Michael Thompson McCann

This tutorial covers biomedical image reconstruction, from the foundational concepts of system modeling and direct reconstruction to modern sparsity and learning-based approaches. Imaging is a critical tool in biological research and medicine, and most ima ...

2019

Kernel Modeling Super-Resolution on Real Low-Resolution Images

Sabine Süsstrunk, Ruofan Zhou

Deep convolutional neural networks (CNNs), trained on corresponding pairs of high- and low-resolution images, achieve state-of-the-art performance in single-image super- resolution and surpass previous signal-processing based approaches. However, their per ...

IEEE COMPUTER SOC2019

Fourier-Domain Optimization for Image Processing

Sabine Süsstrunk, Radhakrishna Achanta, Majed El Helou, Frederike Dümbgen

Image optimization problems encompass many applications such as spectral fusion, deblurring, deconvolution, dehazing, matting, reflection removal and image interpolation, among others. With current image sizes in the order of megabytes, it is extremely exp ...

arXiv2018

Computational Aesthetics and Image Enhancements using Deep Neural Networks

Bin Jin

Imaging devices have become ubiquitous in modern life, and many of us capture an increasing number of images every day. When we choose to share or store some of these images, our primary selection criterion is to choose the most visually pleasing ones. Yet ...

EPFL2018

Deep Convolutional Neural Network for Ultrasound Image Enhancement

Jean-Philippe Thiran, Marcel Arditi, Adrien Georges Jean Besson, Dimitris Perdios, Florian Martinez, Manuel Vonlanthen

The problem of improving image quality in ultrafast ultrasound (US) imaging by means of regularized iterative algorithms has raised a vast interest in the US community. These approaches usually rely on standard image processing priors, such as wavelet spar ...

IEEE2018

Privacy-Friendly Photo Sharing and Relevant Applications Beyond

Lin Yuan

Popularization of online photo sharing brings people great convenience, but has also raised concerns for privacy. Researchers proposed various approaches to enable image privacy, most of which focus on encrypting or distorting image visual content. In this ...

EPFL2017

High-Quality Parallel-Ray x-Ray CT Back Projection Using Optimized Interpolation

Michaël Unser, Michael Thompson McCann

We propose a new, cost-efficient method for computing back projections in parallel-ray X-ray CT. Forward and back projections are the basis of almost all X-ray CT reconstruction methods, but computing these accurately is costly. In the special case of para ...

2017

Revealing Information by Averaging

Sabine Süsstrunk, Roger Hersch, Mahmut Sami Arpa

We present a method for hiding images in synthetic videos and reveal them by temporal averaging. The main challenge is to develop a visual masking method that hides the input image both spatially and temporally. Our masking approach consists of temporal an ...

Optical Soc Amer2017