Atmospheric chemical species detection using multispectral imaging

A computing system for optically detecting a subject chemical species within an atmospheric environment, the computing system comprising:

• a logic machine;
• and
• a storage machine having instructions stored thereon executable by the logic machine to:
• obtain image data representing multispectral imagery of a geographic region captured through the atmospheric environment via an aeronautical vehicle,
• the image data including an array of band-specific intensity values for each of a plurality of spectral bands, including a plurality of reference spectral bands and a sample spectral band having increased sensitivity to the subject chemical species as compared to the plurality of reference spectral bands;
• remove albedo background from the image data for each of the plurality of spectral bands to obtain a normalized array of band-specific intensity values for each of the plurality of spectral bands;
• generate a background reflectance map that includes an array of inter-band intensity values in which each inter-band intensity value represents a filtered combination of band-specific intensity values of the normalized arrays for a grouped subset of the plurality of reference spectral bands;
• compare the normalized array of band-specific intensity values for the sample spectral band to the background reflectance map to obtain an index array of intensity variance values;
• and
• output the index array for the subject chemical species.

A computing system for optically detecting a subject chemical species within an atmospheric environment, the computing system comprising:

• a storage machine having instructions stored thereon executable by a logic machine to:
• obtain image data representing multispectral imagery of a geographic region captured through the atmospheric environment via an aeronautical vehicle,
• the image data including an array of band-specific intensity values for each of a plurality of spectral bands, including a plurality of reference spectral bands and a sample spectral band having increased sensitivity to the subject chemical species as compared to the plurality of reference spectral bands;
• perform spatial anti-aliasing of the image data;
• remove albedo background from the image data following the spatial anti-aliasing for each of the plurality of spectral bands to obtain a normalized array of band-specific intensity values for each of the plurality of spectral bands;
• generate a background reflectance map that includes an array of inter-band intensity values in which each inter-band intensity value represents a filtered combination of band-specific intensity values of the normalized arrays for a grouped subset of the plurality of reference spectral bands;
• compare the normalized array of band-specific intensity values for the sample spectral band to the background reflectance map to obtain an index array of intensity variance values;
• compare each intensity variance value of the index array to a variance threshold to obtain an image mask that distinguishes intensity variance values that are less than the variance threshold from other intensity variance values that are greater than the variance threshold;
• and
• output the image mask.