Abstract: Determining imposition of printable objects (105, 110, 115, 120, and 125) with variable dimensions. A plurality of printable objects (105, 110, 115, 120 and 125) are received (202), at a computer system, to be printed on a medium, wherein the plurality of printable objects comprise a plurality of dimensions. A print layout (150) is determined (204), at the computer system, for the plurality of printable objects such that the print layout comprises a plurality of sub layouts (155 and 160) wherein each of the plurality of sub layouts comprises at least one printable object and wherein at least one sub layout can be separated from the plurality of the sub layouts using an end to end cut of the medium that parallels an edge of the medium.

Abstract: A method for protecting a communication network against failure, comprising the steps of: a) obtaining a primary network, represented by a graph of nodes and links, wherein each link has an associated capacity; b) computing a backup network, that includes nodes of the primary network and links that are not in the primary network; c) when a link of the primary network fails, rerouting communication traffic, through one or more links of the backup network, in order to bypass the failed link. Methods are suggested to determine the backup network, one method relates to expressing the objective and constraints on the backup network as linear or integer expressions, and a linear or integer programming tool is used to solve the equation system and provide optimal backup network.

Abstract: Method and system embodiments of the present invention are directed to restoration of corrupted images using spatial-domain image-processing methods that can effectively employ spatial-domain information both in order to avoid various types of artifacts and distortions produced by frequency-domain image-processing operations and to achieve computational efficiency. The various method and system embodiments of the present invention employ a family of penalty functions to constrain iterative restoration images corrupted by both deterministic corruptions, such as motion-induced blur and blurring due to optical misalignment, incorrect positioning of optical components, and defective optical components as well as essentially non-deterministic noise corruption introduced at various stages of image acquisition, image encoding, image storage, and image transmission.

Abstract: A deblurred digital image is generated from a blurred digital image. The blurred digital image is received. The blurred digital image has a number of objects and a number of edges. Each edge demarcates boundaries of two of the objects. One or more selected edges within the blurred digital image are identified. The selected edges are blurry within the blurred digital image but were originally sharp edges. A blur kernel is determined based on the identified selected edges. The blur kernel denotes how the blurred digital image is blurry. The blur kernel is applied to the blurred digital image to generate the deblurred digital image. The deblurred digital image is output.

Abstract: A method of reducing blurring in an image of size greater than M columns by N rows of pixels, comprises deriving a blur kernel k representing the blur in the image, and deriving an inverse blur kernel k?1. The inverse blur kernel is given by (I) where h(m) is the sum of the first m terms of the series (II) ? is the Dirac delta, m is greater than 1, and h(m) is a two dimensional matrix of size M×N. The two dimensional matrix h(m) is convolved with the image over the whole image in the image pixel domain to produce an image with reduced blur. The method may be applied to a video sequence allowing the sequence of images to be deblurred in real time.

Abstract: A method for determining with a physical image processing device a visual balance of an image includes assigning a visual weight point to each of a plurality of visual elements within the image with the image processing device, each visual weight point having a weight value based on visual properties associated with the visual element, and determining the visual balance of the image with the image processing device by measuring a vector value at a center of the composition, the vector value being based on a distance of each visual weight point from the center and the weight value associated with each visual weight point.

Abstract: Automated imposition wherein a print job comprises multiple documents, and the documents comprise pages having different dimensions. Pages of different dimensions of the same document may be imposed on a single sheet, and pages of equal dimensions may be lined up in a layer across the sheet, forming a cut line along the layer and across the sheet.

Abstract: A method and apparatus (70) is provided for estimating blur degradation of an image (75) that includes a specular highlight. A specular highlight in the image is first identified (77), for example with user assistance. A blur kernel is then derived by extracting (78A) the identified specular highlight as foreground from the image (75) and using the extracted foreground as the blur kernel (78C). The image (75) can then be deblurred by deconvolution (79) with the derived blur kernel.

Abstract: In a method for estimating a point spread function of an image capture device, a first function representing a captured version of a first test image is obtained, where the first test image containing a substantially ideal vertical transition. A second function representing a captured version of a second test image is also obtained, where the second test image contains a substantially ideal horizontal transition. In addition, the point spread function is estimated from the first function and the second function. Also disclosed herein is a method for image degradation compensation that employs the method for estimating a point spread function.

Abstract: A computer implemented method of generating a harmonic image based on object data defining a plurality of objects to be located in the image, and location data defining a plurality of locations in the image, the method comprising the steps of: determining a plurality of harmonic object-location pairs from a plurality of possible object-location pairs; and, generating an image according to the determined harmonic object-location pairs.

Abstract: A method for reducing blur from an image is described. The method includes accessing a blurred image, wherein the blurred image has a width and a length that can be different. The method further includes converting the blurred image into a frequency domain representation of the blurred image and determining an angle of blur from the frequency domain of the blurred image. The method further includes rotating the frequency domain representation of the blurred image by the angle of blur and determining a size of the blur from the rotated frequency domain representation of the blurred image. The method further includes determining a blur kernel associated with the blur, the blur kernel comprising the angle of blur and the size of said blur and de-convoluting the blurred image according to the blur kernel to reduce the blur.

Abstract: Method and system embodiments of the present invention are directed to restoration of corrupted images using spatial-domain image-processing methods that can effectively employ spatial-domain information both in order to avoid various types of artifacts and distortions produced by frequency-domain image-processing operations and to achieve computational efficiency. The various method and system embodiments of the present invention employ a family of penalty functions to constrain iterative restoration images corrupted by both deterministic corruptions, such as motion-induced blur and blurring due to optical misalignment, incorrect positioning of optical components, and defective optical components as well as essentially non-deterministic noise corruption introduced at various stages of image acquisition, image encoding, image storage, and image transmission.

Abstract: A method for reducing blur from an image is described. The method includes accessing a blurred image, wherein the blurred image has a width and a length that can be different. The method further includes converting the blurred image into a frequency domain representation of the blurred image and determining an angle of blur from the frequency domain of the blurred image. The method further includes rotating the frequency domain representation of the blurred image by the angle of blur and determining a size of the blur from the rotated frequency domain representation of the blurred image. The method further includes determining a blur kernel associated with the blur, the blur kernel comprising the angle of blur and the size of said blur and de-convoluting the blurred image according to the blur kernel to reduce the blur.

Abstract: A method for protecting a communication network against failure, comprising the steps of: a) obtaining a primary network, represented by a graph of nodes and links, wherein each link has an associated capacity; b) computing a backup network, that includes nodes of the primary network and links that are not in the primary network; c) when a link of the primary network fails, rerouting communication traffic, through one or more links of the backup network, in order to bypass the failed link. Methods are suggested to determine the backup network, one method relates to expressing the objective and constraints on the backup network as linear or integer expressions, and a linear or integer programming tool is used to solve the equation system and provide optimal backup network. Another method relates to an algorithm that traverses the links of the primary network, and adds a link having an equal capacity to the backup network as long as no cycle is created.