Hyperspectral imaging devices using hybrid vector and tensor processing

A method comprising:

• obtaining data representative of a scene across spectral bands using a compressive-sensing-based hyperspectral imaging system comprising optical elements;
• sampling two modes of a three-dimensional tensor corresponding to a hyperspectral representation of said scene using sampling matrices, one for each of said two modes, to generate a modified three-dimensional tensor;
• after said sampling two modes, sampling a third mode of said modified three-dimensional tensor using a third sampling matrix to generate a further modified three-dimensional tensor;
• and
• reconstructing hyperspectral data from said further modified three-dimensional tensor using said sampling matrices and said third sampling matrix,
• said sampling two modes of a three-dimensional tensor being performed by measuring light intensity, resulting samples being represented by digital data, and said sampling a third mode of said modified three-dimensional tensor being performed by processing said digital data.

A method comprising:

• obtaining data representative of a scene across spectral bands using a compressive-sensing-based hyperspectral imaging system comprising optical elements;
• sampling two modes of a three-dimensional tensor corresponding to a hyperspectral representation of said scene using said compressive-sensing-based hyperspectral imaging system, to generate a modified three-dimensional tensor;
• after said sampling two modes, sampling a third mode of said modified three-dimensional tensor using an external processor separate from said compressive-sensing-based hyperspectral imaging system to generate a further modified three-dimensional tensor;
• and
• reconstructing hyperspectral data from said further modified three-dimensional tensor using said external processor,
• said reconstructing comprising recovering each mode of said three-dimensional tensor via a sequence of optimization processing in a reverse order of said sampling two modes and said sampling a third mode, said sequence comprising:
• applying an optimization process to said further modified three-dimensional tensor to reconstruct said modified three-dimensional tensor as a recovered modified three-dimensional tensor;
• and
• applying an optimization process to said recovered modified three-dimensional tensor to reconstruct said three-dimensional tensor corresponding to said data representative of said scene.

A method comprising:

• obtaining data representative of a scene across spectral bands using a compressive-sensing-based hyperspectral imaging system comprising optical elements;
• sampling two modes of a three-dimensional tensor corresponding to a hyperspectral representation of said scene using said compressive-sensing-based hyperspectral imaging system, to generate a modified three-dimensional tensor;
• after said sampling two modes, sampling a third mode of said modified three-dimensional tensor using an external processor separate from said compressive-sensing-based hyperspectral imaging system to generate a further modified three-dimensional tensor;
• and
• reconstructing hyperspectral data from said further modified three-dimensional tensor using said external processor,
• said sampling two modes of a three-dimensional tensor being performed by measuring light intensity, and resulting samples being represented by digital data.

A system comprising:

• a compressive-sensing-based hyperspectral imaging system comprising:
• optical elements obtaining data representative of a scene;
• and
• a image processor operatively connected to said optical elements,
• said compressive-sensing-based hyperspectral imaging system sampling two modes of a three-dimensional tensor corresponding to a hyperspectral representation of said scene using sampling matrices, one for each of said two modes, to generate a modified three-dimensional tensor,
• said image processor sampling a third mode of said modified three-dimensional tensor using a third sampling matrix to generate a further modified three-dimensional tensor after said compressive-sensing-based hyperspectral imaging system performs said sampling two modes, and
• said image processor reconstructing hyperspectral data from said further modified three-dimensional tensor using said sampling matrices and said third sampling matrix,
• said image processor reconstructing hyperspectral data by recovering each mode of said three-dimensional tensor via a sequence of optimization processing in a reverse order of said sampling two modes and said sampling a third mode, said sequence comprising:
• applying an optimization process to said further modified three-dimensional tensor to reconstruct said modified three-dimensional tensor as a recovered modified three-dimensional tensor;
• and
• applying an optimization process to said recovered modified three-dimensional tensor to reconstruct said three-dimensional tensor corresponding to said data representative of said scene.

A system comprising:

• a compressive-sensing-based hyperspectral imaging system comprising:
• optical elements obtaining data representative of a scene;
• and
• a image processor operatively connected to said optical elements,
• said compressive-sensing-based hyperspectral imaging system sampling two modes of a three-dimensional tensor corresponding to a hyperspectral representation of said scene using sampling matrices, one for each of said two modes, to generate a modified three-dimensional tensor,
• said image processor sampling a third mode of said modified three-dimensional tensor using a third sampling matrix to generate a further modified three-dimensional tensor after said compressive-sensing-based hyperspectral imaging system performs said sampling two modes, and
• said image processor reconstructing hyperspectral data from said further modified three-dimensional tensor using said sampling matrices and said third sampling matrix,
• said compressive-sensing-based hyperspectral imaging system sampling said two modes by measuring light intensity, and resulting samples being represented by digital data.

A system comprising:

• a compressive-sensing-based hyperspectral imaging system comprising optical elements obtaining data representative of a scene, and a image processor;
• and
• an external processor separate from and operatively connected to said compressive-sensing-based hyperspectral imaging system,
• said compressive-sensing-based hyperspectral imaging system sampling two modes of a three-dimensional tensor corresponding to a hyperspectral representation of said scene to generate a modified three-dimensional tensor;
• said image processor outputting said modified three-dimensional tensor to said external processor;
• said external processor sampling a third mode of said modified three-dimensional tensor to generate a further modified three-dimensional tensor after said compressive-sensing-based hyperspectral imaging system performs said sampling two modes;
• and
• said external processor reconstructing hyperspectral data from said further modified three-dimensional tensor,
• said external processor reconstructing hyperspectral data by recovering each mode of said three-dimensional tensor via a sequence of optimization processing in a reverse order of said sampling two modes and said sampling a third mode, said sequence comprising:
• applying an optimization process to said further modified three-dimensional tensor to reconstruct said modified three-dimensional tensor as a recovered modified three-dimensional tensor;
• and
• applying an optimization process to said recovered modified three-dimensional tensor to reconstruct said three-dimensional tensor corresponding to said data representative of said scene.

A system comprising:

• a compressive-sensing-based hyperspectral imaging system comprising optical elements obtaining data representative of a scene, and a image processor;
• and
• an external processor separate from and operatively connected to said compressive-sensing-based hyperspectral imaging system,
• said compressive-sensing-based hyperspectral imaging system sampling two modes of a three-dimensional tensor corresponding to a hyperspectral representation of said scene to generate a modified three-dimensional tensor;
• said image processor outputting said modified three-dimensional tensor to said external processor;
• said external processor sampling a third mode of said modified three-dimensional tensor to generate a further modified three-dimensional tensor after said compressive-sensing-based hyperspectral imaging system performs said sampling two modes;
• and
• said external processor reconstructing hyperspectral data from said further modified three-dimensional tensor,
• said compressive-sensing-based hyperspectral imaging system sampling said two modes by measuring light intensity, resulting samples being represented by digital data, and said external processor sampling said third mode by processing said digital data.