Navigasjon

  • Hopp til innhold
NTNU Hjemmeside

NTNU SmallSat Lab

  • Home
  • About
    • Team
    • Organization
    • Observational Pyramid
    • Contacts
    • Facilities
    • Events
  • Research & Projects
    • Publications
    • DiverSEA
    • System-of-Systems
    • HYPSCI
    • ARIEL
    • AWAS
    • Supporting Projects
    • Awards
    • AuroraSpace
    • Green Platform
    • Past Projects
  • For Students
    • Project and Master Subjects 2025-2026
    • Past Projects
  • Missions
    • HYPSO-1
    • HYPSO-2
    • HYPSO-3
    • GNSS-R
  • Data & Software
    • Python for HYPSO
    • Labeld Data
    • Raw Data
  1. NTNU SmallSat Lab
  2. Data & Software
  3. Python for HYPSO

Språkvelger

Python for HYPSO

×
  • Python for HYPSO
  • Labeld Data
  • Raw Data
MENY

HYPSO Python Package

The HYPSO Toolbox for Hyperspectral Image Processing

For researchers delving into the world of hyperspectral imaging, particularly those focusing on marine environments, the HYPSO satellite mission provides relevant data. HYPSO-1, launched in 2022, and its successor, HYPSO-2, collect data using a special type of camera that captures hyperspectral images. This allows for detailed Earth surface analysis, such as our oceans. To simplify the data handling of the HYPSO images, we developed the HYPSO Toolbox. This Python package enables you to process images captured by the HYPSO satellites.

The HYPSO Toolbox provides researchers with a set of functionalities for working with hyperspectral imagery, such as:

  • Data Ingestion: import and load HYPSO-1 and HYPSO-2 image data for further processing.
  • Pre-processing: Essential steps like radiometric calibration and atmospheric correction are available through the toolbox.
  • Spectral Analysis: The toolbox provides tools to leverage the spectral information within the images. This involves techniques related to band manipulation, spectral unmixing, and identification of specific materials based on their unique spectral signatures.
  • Visualization: Effective data visualization is crucial for scientific exploration. The toolbox offers functionalities to create clear and informative visualizations of the processed hyperspectral data.

Documentation for the toolbox can be found here. The soruce code can be viewed here. 

NTNU – Norges teknisk-naturvitenskapelige universitet

  • For ansatte
  • |
  • For studenter
  • |
  • Innsida
  • |
  • Blackboard

Studere

  • Om studier
  • Studieprogram
  • Emner
  • Videreutdanning
  • Karriere

Aktuelt

  • Nyheter
  • Arrangement
  • Jobbe ved NTNU

Om NTNU

  • Om NTNU
  • Bibliotek
  • Strategi
  • Forskning
  • Satsingsområder
  • Innovasjon
  • Organisasjonskart
  • Utdanningskvalitet

Kontakt

  • Kontakt oss
  • Finn ansatte
  • Spør en ekspert
  • Pressekontakter
  • Kart

NTNU i tre byer

  • NTNU i Gjøvik
  • NTNU i Trondheim
  • NTNU i Ålesund

Om nettstedet

  • Bruk av informasjonskapsler
  • Tilgjengelighetserklæring
  • Personvern
  • Ansvarlig redaktør
Facebook Instagram Linkedin Snapchat Tiktok Youtube
Logg inn
NTNU logo