New layers in JMARS for displaying enhanced stereo and disparity images of Mastcam

Chiman Kwan; Bence Budavari; Bulent Ayhan; Scott Dickenshied

doi:10.1117/12.2557816

24 April 2020 New layers in JMARS for displaying enhanced stereo and disparity images of Mastcam

Chiman Kwan, Bence Budavari, Bulent Ayhan, Scott Dickenshied

Proceedings Volume 11392, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXVI; 1139204 (2020) https://doi.org/10.1117/12.2557816
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

The Mastcam multispectral imagers onboard the Mars rover Curiosity have been collecting data since 2012. There are two imagers onboard the rover. The left imager has a wide field of view, but three times lower resolution than that of the right, which is just the opposite. Left and right images can be combined to generate stereo and disparity images. However, the resolution of the stereo images using conventional ways is at the same resolution of the left. Ideally, it will be more interesting to science fans and rover operators if one can generate stereo images with the same resolution of the right imager, as the resolution will be three times better. Recently, we have developed some algorithms that can fuse left and right images to create left images with the same resolution of the right. Consequently, high resolution stereo images can be generated. Moreover, disparity images can also be generated. In this document, we will summarize the development of new JMARS layers that display the enhanced left images using pansharpening and deep learning algorithms, high resolution stereo images, and high resolution disparity maps. The details of the workflow will be described. Some demonstration examples will be given as well.

Citation Download Citation

Chiman Kwan, Bence Budavari, Bulent Ayhan, and Scott Dickenshied "New layers in JMARS for displaying enhanced stereo and disparity images of Mastcam", Proc. SPIE 11392, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXVI, 1139204 (24 April 2020); https://doi.org/10.1117/12.2557816

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KEYWORDS

Image resolution

Imaging systems

Image enhancement

Databases

Algorithm development

Image fusion

Image compression

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