USA As Represented by Secretary of the Navy

Andrey V Kanaev

Erin F Fleet

Dean A Scribner

John R Ackerman

Christopher W Miller

Jeremy Murray-Krezan

A computer-implemented demosaicking system and method that can receive an image (or many images that represent individual frames of a video) at a demosaicking processor from a multi-spectral band camera. The image can include four or more band images that each correspond to an unique spectral band obtained by the multi-spectral band camera. A clustering module can perform spectral clustering of the four or more band images to identify multiple clusters. For each of the plurality of clusters, a weights module can determine a cluster weight by computing correlations between each of the unique spectral bands in each cluster. A super-resolution module can perform super-resolution for each of the unique spectral bands by utilizing the cluster weights from the weights module. The super-resolution module can iteratively apply the super-resolution for each of the unique spectral bands and a value for each unique spectral band can be updated after each iteration.

Demosaicking system and method for color array based multi-spectral sensors

A computer implemented method is provided for computing a two-way optical flow between a reference frame and one or more associated frames in an optical flow module. A forward warping operator and a backward warping operator can be generated between the reference frame and each of the one or more associated frames in a warping module. The forward warping operator and the backward warping operator provide motion compensation between the frames. Weights for each of the forward warping operators and the backward warping operators can be computed in a weight module. The weights correspond to uncertainty of motion estimation. A super resolution iteration algorithm can be calculated in a super-resolution iteration module.

Multi-frame super-resolution of image sequence with arbitrary motion patterns

A spectral anomaly detection method includes the steps of segmenting a panchromatic image, obtained from a hyperspectral sensor into cluster data sets. Principal component analysis can be separately performed on each of the cluster data sets to produce a plot of principal components. An anomaly detection algorithm can be applied to an adaptively selected subset of principal components for each of the cluster data sets to produce cluster detection scores. Finally, separate detection thresholding algorithms can be applied to each of the cluster detection scores, and the results of the detection thresholding algorithms can be combined into a single detection plane.

Spectral anomaly detection in deep shadows

A method and system is provided for performing high-resolution image assembly regardless of observed scene content. An imaging system, including a focal plane array and lenslet array can be calibrated to account for subimage shifts. A calibration module can determine the subimage shifts by calculating an average point source position reference point coordinates for each of the subimages, and then determining the difference between the average point source position and the reference point coordinates for each subimage. The imaging system can then be calibrated utilizing the subimage shifts for each of the plurality of subimages. Finally, an assembly module can perform a high-resolution image assembly with the calibrated imaging system.

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Lorton, VA, United States of America

Andrey V Kanaev