Abstract: The disclosure concerns hyperspectral and multispectral image. The disclosure concerns the computation of a descriptor for such an image. The descriptor can be used in a range of image post-processing applications, such as classification, recognition, tracking and localization. Aspects of the invention include a computer implemented method and a computer system. To computer the descriptor for a set of wavelength indexed bands, a band representation of the radiance measurements for that band based on a probability distribution function is computed 300. Then a wavelength-dependent cross-correlation between the band representations is computed 302. Finally, a descriptor based on the computed cross-correlation between the band representations is computed 304. It is an advantage that the descriptor captures a discriminative and descriptive representation of scene captured in the hyperspectral or multispectral image.

Abstract: The disclosure concerns processing of electronic images, such as hyperspectral, or multispectral images. In particular, but is not limited to, a method, software and computer for estimating shape information or a photometric invariant of a location of image of a scene. The image data (300) indexed by wavelength ? and polarisation filter angle ?. For each wavelength ? index, a polarisation angle ? is estimated from the image data (300) by the processor (810). The processor (810) then also estimates the shape information (such as azimuth a, zenith ?, or surface normal) or photometric invariants (such as refractive index) based on the estimated polarisation angle cp for each wavelength index ?. Greater accuracies can be achieved in the estimated shape information and/or photometric invariants by using wavelength-indexed data. Further, surface information or photometric invariant can be estimated based upon polarisation in a single-view hyperspectral or multi-spectral imagery.

Abstract: The disclosure concerns processing of electronic images, such as hyperspectral or multispectral images. In particular, but is not limited to methods, software and computer systems for determining underlying spectra of an image of a scene. The image data comprises for each pixel location a sampled image spectrum that is a mixture of plural reflectance spectra. Processor 310 determines or accesses plural hyperplanes that each have plural linearly independent basis vectors. Each hyperplane represents an estimate of one of the plural reflectance spectra. The processor 310 then determines for each pixel location, a contribution of the plural basis vectors of each hyperplane to the image spectrum of that pixel location. The processor 310 determines or accesses plural hyperplanes and not plural endmembers directly. Hyperplanes are two-dimensional while endmembers are only one-dimensional. As a result, hyperplanes carry more information, such as the illumination spectrum and are therefore of greater use.

Abstract: The disclosure concerns processing of electronic images, such as hyperspectral, multispectral or trichromatic images. In particular, but is not limited to, a method, software and computer for estimating parameters of a reflectance model applied to an image is disclosed. Examples of processing of the images using the estimated parameters includes material recognition, re-colouring and re-shading of objects represented in the image. That is, a computer implemented method is provided of estimating one or more of photogrammetric parameters, ?(u) surface shape N and index of refraction n(u,?) represented in a reflectance image having one or more known illumination directions and a known viewing direction V, the method comprising optimising (802) the difference between the reflectance image and a reflectance model, the reflectance model being based on surface shape N; the material index of refraction n(u,?) and a set of photogrammetric parameters ?(u).

Abstract: The disclosure concerns processing of electronic images, such as hyperspectral or multispectral images. Processing of the images includes object recognition and image enhancement in a way that harnesses the information available from the image based on the wavelength indexed spectral data these types of images provide. Illumination spectrum of such an image is estimated (FIG. 21) using a cost function based on a dichromatic reflection model and a constraint term. This method may be performed on sub-images of the image. A method for selecting these sub-images (FIG. 23) is also disclosed. A method of determining photometric parameters of the image given the estimated illumination spectrum (FIG. 22) is also disclosed.

Abstract: The disclosure concerns hyperspectral and multispectral image. The disclosure concerns the computation of a descriptor for such an image. The descriptor can be used in a range of image post-processing applications, such as classification, recognition, tracking and localisation. Aspects of the invention include a computer implemented method and a computer system. To computer the descriptor for a set of wavelength indexed bands, a band representation of the radiance measurements for that band based on a probability distribution function is computed 300. Then a wavelength-dependent cross-correlation between the band representations is computed 302. Finally, a descriptor based on the computed cross-correlation between the band representations is computed 304. It is an advantage that the descriptor captures a discriminative and descriptive representation of scene captured in the hyperspectral or multispectral image.

Abstract: The invention concerns the compact representation of a reflectance spectrum of a material. For example, for in compression, identification and comparison of reflectance spectrum data of multiple materials. The compressed representation interpolating a spline curve to the reflectance spectrum data, the spline curve having a set of control points, a knot vector, and representing wavelength and reflectance as functions of an independent parameter (42). Then removing one or more knots from the knot vector that minimise a cost function in a parameter domain of the spline curve based on the wavelength function (44). Aspects of the invention include a method, software, a computer system and the compact representation itself.