Abstract: An image processing method is disclosed, comprising: receiving a plurality of images of an object; and, for each image, determining a brightness value for each point on the object that is visible, and generating a tile grid for the image. Each point that is visible in an image corresponds to one tile in the tile grid. For each tile pair where at least one point is visible in both tiles of the tile pair, a brightness offset value is determined. For each image, an offset matrix is generated. Values of the offset matrix comprise brightness offsets to apply to each tile of a tile grid for the image to normalize the brightness of the image with the other images. A plurality of reconstructed images is generated based on performing, for each image, transformation operations on the given image based on the corresponding offset matrix to generate a reconstructed image.

Abstract: A portable development and execution framework for processing media objects. The framework involves: accepting an instruction to perform a media processing function; accepting a media object to be associated with the media processing function; wrapping the media object with an attribute that specifies a type and format of the media object, and a hardware domain associated with the media object; and causing an execution domain to perform the media processing function on the media object. The instruction to perform the media processing function is expressed in a form that is independent of the hardware domain associated with the media object, and may also be independent of the type and format of the media object. The media object may be an image, and the media processing function may include an image processing function performed on a GPU.

Abstract: A portable development and execution framework for processing media objects. The framework involves: accepting an instruction to perform a media processing function; accepting a media object to be associated with the media processing function; wrapping the media object with an attribute that specifies a type and format of the media object, and a hardware domain associated with the media object; and causing an execution domain to perform the media processing function on the media object. The instruction to perform the media processing function is expressed in a form that is independent of the hardware domain associated with the media object, and may also be independent of the type and format of the media object. The media object may be an image, and the media processing function may include an image processing function performed on a GPU.

Abstract: A portable development and execution framework for processing media objects. The framework involves: accepting an instruction to perform a media processing function; accepting a media object to be associated with the media processing function; wrapping the media object with an attribute that specifies a type and format of the media object, and a hardware domain associated with the media object; and causing an execution domain to perform the media processing function on the media object. The instruction to perform the media processing function is expressed in a form that is independent of the hardware domain associated with the media object, and may also be independent of the type and format of the media object. The media object may be an image, and the media processing function may include an image processing function performed on a GPU.

Abstract: The present invention provides a Fast Moiré Interferometry (FMI) method and system for measuring the height profile of an object with an increase precision by combining a plurality of image features. In one large aspect of the invention, two or several images are acquired under different conditions, to yield two or several images: Ia?(x,y), Ia?(x,y), . . . instead of one single image Ia(x,y). This is repeated for images obtained with different grating projection “b”, “c”, and “d”. These images are combined to provide combined images or a merged phase value, which are used to determine the object height profile.