Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for determining illumination information in an image. According to a feature of the present invention, the method comprises the steps of identifying depth information in the image, identifying spatio-spectral information for the image, as a function of the depth information and utilizing the spatio-spectral information to identify illumination flux in the image.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for an automatic chromatic aberration correction. The method comprises the steps of setting a range of test correction factors, applying the test correction factors of the range, incrementally, to a test block of the image, measuring chromatic aberration error at the test block after application of each of the test correction factors, and selecting a test correction factor having a lowest chromatic aberration error.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method for learning object recognition in an image is provided. According to a feature of the present invention, the method comprises the steps of providing a training set of standard images, calculating intrinsic images corresponding to the standard images and building a classifier as a function of the intrinsic images.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of providing an image file depicting an image, in a computer memory, performing an image segregation operation on the image file to generate a set of intrinsic images corresponding to the image, modifying a preselected one of the set of intrinsic images according to a set of preselected operations and merging the modified one of the set of intrinsic images relative to the set of intrinsic images to provide a modified output image.

Abstract: In an exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of converting a color band representation of the image to a homogeneous representation of spectral and spatial characteristics of a texture region in the image and utilizing the homogeneous representation of spectral and spatial characteristics of a texture region in the image to identify homogeneous tokens in the image.

Abstract: In an exemplary embodiment of the present invention, an automated, computerized method is provided for classifying pixel values in a motion sequence of images. According to a feature of the present invention, the method comprises the steps of determining spectral information relevant to the sequence of images, and utilizing the spectral information to classify a pixel as one of background, shadow and object.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for determining illumination flux in an image. According to a feature of the present invention, the method comprises the steps of performing a computer learning technique to determine spatio-spectral information for the images, and utilizing the spatio-spectral information to identify illumination flux.

Abstract: In an exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of providing an image, organizing spatio-spectral information for the image in a matrix equation expressed by: [A][x]=[b], wherein [A] expresses values determined by a constraining relationship imposed upon the spatio-spectral information, [b] expresses recorded information for the image, and [x] expresses an unknown material/illumination component of the image, and utilizing the matrix equation in an image segregation operation.

Abstract: In an exemplary embodiment of the present invention, a test bed for optimizing an image segregation is provided. According to a feature of the present invention, the test bed comprises a memory storing an image file containing an image, a set of operations, a set of constraint software modules and a set of parameters relevant to the image, a transform module for performing a preselected one of the set of operations, defined by a preselected one of the set of constraint software modules, on the image, as a function of preselected ones of the set of parameters, to provide an output image, a test module utilizing the transform module output image, an analysis module for analyzing test module performance, and a feedback loop for varying selected ones of the operations, constraint software modules and parameters, for input to the transform module, to provide a new output image for input to the test module.

Abstract: In an exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of generating spatio-spectral information for the image, defining a constraint as a function of the spatio-spectral information, and performing an optimization operation as a function of the constraint to generate an intrinsic image corresponding to the image.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for determining an illumination boundary in an image. The method comprises the steps of performing dynamic sampling in preselected local areas of the image to determine spectral ratio information for the image at each of the preselected local areas, and utilizing the spectral ratio information to identify an illumination boundary.

Abstract: In an exemplary embodiment of the present invention, an automated, computerized method is provided for classifying pixel values in a motion sequence of images. According to a feature of the present invention, the method comprises the steps of determining spectral information relevant to the sequence of images, and utilizing the spectral information to classify a pixel as one of background, shadow and object.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the step of performing a filter response technique to identify patches of uniform reflectance within the image. In a further exemplary embodiment, the method comprises the additional step of utilizing the identified patches of uniform material reflectance to generate single material token regions for use in processing material and illumination aspects of the image.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of providing an image file, identifying a boundary in the image, calculating a representation of the boundary extending to segments of the image at either side of the boundary, performing feature calculations on the representation and classifying the boundary as caused by a material change, as a function of the feature calculations.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method for generating an illumination invariant, chromaticity representation of an image is provided. The method of the present invention comprises the steps of providing an image comprising an array of pixels, each pixel having N band color values, transforming the N bands to log color space values in a log color space, generating a bi-illuminant chromaticity plane in the log color space and projecting the log color space values to the chromaticity the plane to provide chromaticity representation values corresponding to the pixels of the image.

Abstract: In an exemplary embodiment of the present invention, an automated, computerized method is provided for classifying pixel values in a motion sequence of images. According to a feature of the present invention, the method comprises the steps of determining spectral information relevant to the sequence of images, and utilizing the spectral information to classify a pixel as one of background, shadow and object.

Abstract: In an exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of converting a color band representation of the image to a homogeneous representation of spectral and spatial characteristics of a texture region in the image and utilizing the homogeneous representation of spectral and spatial characteristics of a texture region in the image to identify homogeneous tokens in the image.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of identifying token regions in the image, each token region comprising a connected image region of similar color and intensity, and utilizing the identified token regions to generate single material token regions for use in processing material and illumination aspects of the image.

Abstract: In an exemplary embodiment of the present invention, an image processor is provided. According to a feature of the present invention, the image processor comprises a CPU arranged and configured to receive an image input, the image input depicting a scene, the CPU being further arranged and configured to execute a routine to receive the image input and perform preselected spatio-spectral analysis of the image to create a version of the image input optimized for analysis of the scene.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of generating a gradient representation of the image, and normalizing the gradient representation to generate an illumination-invariant gradient representation of the image.