Integrating Novelty Detection Capabilities with MSL Mastcam Operations to Enhance Data Analysis

TL;DR

This paper introduces a novelty detection system integrated with MSL Mastcam operations to rapidly identify unusual features in multispectral images, aiding quick data analysis and discovery during Mars rover missions.

Contribution

The paper presents a novel application of novelty detection to multispectral Mastcam data, enabling rapid triage and highlighting of atypical features for Mars rover operations.

Findings

Colorized heat maps effectively highlight novel regions.

Novelty scores help prioritize data for analysis.

System accelerates identification of diagnostic features.

Abstract

While innovations in scientific instrumentation have pushed the boundaries of Mars rover mission capabilities, the increase in data complexity has pressured Mars Science Laboratory (MSL) and future Mars rover operations staff to quickly analyze complex data sets to meet progressively shorter tactical and strategic planning timelines. MSLWEB is an internal data tracking tool used by operations staff to perform first pass analysis on MSL image sequences, a series of products taken by the Mast camera, Mastcam. Mastcam's multiband multispectral image sequences require more complex analysis compared to standard 3-band RGB images. Typically, these are analyzed using traditional methods to identify unique features within the sequence. Given the short time frame of tactical planning in which downlinked images might need to be analyzed (within 5-10 hours before the next uplink), there exists a need to triage analysis time to focus on the most important sequences and parts of a sequence. We address this need by creating products for MSLWEB that use novelty detection to help operations staff identify unusual data that might be diagnostic of new or atypical compositions or mineralogies detected within an imaging scene. This was achieved in two ways: 1) by creating products for each sequence to identify novel regions in the image, and 2) by assigning multispectral sequences a sortable novelty score. These new products provide colorized heat maps of inferred novelty that operations staff can use to rapidly review downlinked data and focus their efforts on analyzing potentially new kinds of diagnostic multispectral signatures. This approach has the potential to guide scientists to new discoveries by quickly drawing their attention to often subtle variations not detectable with simple color composites.