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PIRM2018 Challenge on Spectral Image Super-Resolution: Methods and Results

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Multi-modal Spectral Image Super-Resolution

Sabine Süsstrunk, Ruofan Zhou, Fayez Lahoud

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 ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

Multi-Spectral Widefield Microscopy of the Beating Heart through Post-Acquisition Synchronization and Unmixing

Michael Stefan Daniel Liebling, Christian Jaques

Multi-spectral imaging allows distinguishing biological structures. For cardiac microscopy, available devices are either too slow or require illumination intensities that are detrimental to the sample. We present a method for spectral super-resolution imag ...

IEEE2019

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

Biomedical optical techniques for intracochlear cellular imaging

Marilisa Romito

Imaging the inner ear microanatomy is of great importance for the assessment of the state of the cells responsible for sound detection. Hearing disorders are mainly due to a malfunction of the cochlea, the bone containing the cells inside the inner ear. Un ...

EPFL2019

Short spatial resolutions retrieval from a long pulse BOTDA trace

Luc Thévenaz, Zhisheng Yang, Simon Adrien Zaslawski, Sheng Wang

A novel technique is proposed to obtain a flexible and variable spatial resolution from a conventional Brillouin optical time-domain analyzers using a fast post-processing algorithm. The approach is very attractive since a fine spatial resolution can be ob ...

SPIE2019

PIRM2018 Challenge on Spectral Image Super-Resolution: Methods and Results

Sabine Süsstrunk, Tong Zhang, Dong Liu, Ruofan Zhou, Fayez Lahoud, Radu Timofte, Chang Chen, Soumik Sarkar

In this paper, we describe the Perceptual Image Restoration and Manipulation (PIRM) workshop challenge on spectral image super- resolution, motivate its structure and conclude on results obtained by the participants. The challenge is one of the first of it ...

2018

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Springer2018

In a time of rising concern about climate change and pollution, the water quality of large lakes acts as an indicator of the health of the environment. To study the water quality at a large scale - up to several hundreds of kilometres - hyperspectral remot ...

EPFL2018

Oxygenation is an important marker in many clinical settings, e.g. diagnosing ischaemic brain injuries in preterm infants or determining treatment effectiveness in cancer patients. Despite significant efforts to determine the oxygenation state of the human ...

EPFL2018

Deep Residual Network for Joint Demosaicing and Super- Resolution

Sabine Süsstrunk, Radhakrishna Achanta, Ruofan Zhou

The two classic image restoration tasks, demosaicing and super-resolution, have traditionally always been studied indepen- dently. That is sub-optimal as sequential processing, demosaic- ing and then super-resolution, may lead to amplification of ar- tifac ...

Society for Imaging Science and Technology ( IS&T )2018