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StereoMSI

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About this Collection

StereoMSI


1. Multi-spectral super-resolution dataset (extension to PIRM2018 multi-spectral super-resolution challenge dataset). The dataset includes - 272 training stereo registered multi-spectral RGB image pairs including the original RGB mosaic images. - 970 raw multi-spectral images. These need to be downsampled (x2 or x3 etc.) to create low-resolution im... more


Computer Vision Image Processing Knowledge Representation and Machine Learning


https://doi.org/10.25919/5e17c1f7928d7


2017


2018


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CSIROEnquiries@csiro.au
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Super-resolution SR Multi-spectral RGB


:

Super-resolved Chromatic Mapping of Snapshot Mosaic Image Sensors via a Texture Sensitive Residual Network

Attribution
:

PIRM2018 Challenge on Spectral Image Super-Resolution: Dataset and Study

Attribution

Shoeiby_PIRM2018_Challenge_on_Spectral_Image_Super-Resolution_Dataset_and_Study_ECCVW_2018_paper.pdf


03570154_wavelegnth_in_block


1. Images in the multi-spectral super-resolution dataset are in .tiff format. 2. Images in the colour-prediction dataset are in .tiff (RGB) and .mat (multi-spectral) formats. Converting .mat to .npy can accelerate training. See https://arxiv.org/pdf/1909.02221.pdf for more information on multi-spectral data format.


CSIRO Data Licence


CSIRO (Australia)


Shoeiby, Mehrdad (2019): StereoMSI. v2. CSIRO. Data Collection. https://doi.org/10.25919/5e17c1f7928d7


All Rights (including copyright) CSIRO 2019.


The metadata and files (if any) are available to the public.

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About this Project

AIM FSP_TB07_WP05: Optical sensing for marine environments


Data analytics for marine environments


Janet Anstee





Mehrdad Shoeiby


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