Abstract:
A system and method for generating a mosaic image from respective regions in a plurality of individual images, at least one of the regions being distorted and having a left and/or right edge that is tilted relative to a direction of view of the respective image. The distorted regions are rectified so as to form a respective rectified rectangular region and at least some of the rectified rectangular regions are mosaiced to form the mosaic image.
Abstract:
A method of selecting images for lenticular printing. The method comprises receiving a sequence having a plurality of images, selecting a segment of the sequence according to one or more lenticular viewing measures, and outputting the segment for allowing the lenticular printing.
Abstract:
A method for identifying a blur profile of a multi image display with a first image separating mask. The method comprises displaying a calibration pattern through a second image separating mask, allowing an evaluator to provide a visual estimation indicating a blur brought about to the calibration pattern by the second image separating mask, and generating a blur profile of at least the first image separating mask according to the visual estimation. The first and second image separating masks having a substantially similar optical profile.
Abstract:
A super-resolution enhanced image generating system is described for generating a super-resolution-enhanced image from an image of a scene, identified as image g0, comprising a base image and at least one other image gi, the system comprising an initial super-resolution enhanced image generator, an image projector module and a super-resolution enhanced image estimate update generator module. The initial super-resolution enhanced image generator module is configured to use the image g0 to generate a super-resolution enhanced image estimate. The image projector module is configured to selectively use a warping, a blurring and/or a decimation operator associated with the image gi to generate a projected super-resolution enhanced image estimate. The super-resolution enhanced image estimate update generator module is configured to use the input image gi and the super-resolution enhanced image estimate to generate an updated super-resolution enhanced image estimate.