Enhancing mastcam images for mars rover mission

Minh Dao, Chiman Kwan, Bulent Ayhan, James Bell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

25 Scopus citations


This paper summarizes some new results in improving the left Mastcam images of the Mars Science Laboratory (MSL) onboard the Mars rover Curiosity. There are two multispectral Mastcam imagers, having 9 bands in each. The left imager has wide field of view, but low resolution whereas the right imager is just the opposite. Our goal is to investigate the possibility of fusing the left and right images to form high spatial resolution and high spectral resolution data cube so that stereo images and data clustering performance can be improved. Many pansharpening algorithms have been investigated. Actual Mastcam images were used in our experiments. Preliminary results indicate that the pansharpened images can indeed enhance the data clustering performance using both objective and subjective evaluations.

Original languageEnglish (US)
Title of host publicationAdvances in Neural Networks - ISNN 2017 - 14th International Symposium, ISNN 2017, Proceedings
EditorsFengyu Cong, Qinglai Wei, Andrew Leung
PublisherSpringer Verlag
Number of pages10
ISBN (Print)9783319590806
StatePublished - 2017
Event14th International Symposium on Neural Networks, ISNN 2017 - Sapporo, Hakodate, and Muroran, Hokkaido, Japan
Duration: Jun 21 2017Jun 26 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10262 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other14th International Symposium on Neural Networks, ISNN 2017
CitySapporo, Hakodate, and Muroran, Hokkaido


  • Curiosity rover
  • Image fusion
  • Mastcam
  • Pansharpening

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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