Abstract: A system and method utilize data buffers and data access schedules to improve handling of captured image data of an object under inspection for tomosynthetically processing such captured image data to reconstruct desired cross-sectional images therefrom. One embodiment implements a data buffer communicatively coupled to a radiographic imaging system that allows for storage of captured radiographic image data for at least a portion of multiple different projections of an object under inspection, such as image data associated with one or more angles of view of one or more different regions of the object, and then later that stored data may be used for tomosynthetically reconstructing cross-sectional images for the object under inspection.

Abstract: A distributed computing system and method is provided for executing block diagram software applications across multiple computing devices. A first computing device is configured to execute a first block of a block diagram software application to produce an output. The first computing device transparently communicates with a second computing device to provide the output of the first block to a second block of the block diagram software application resident on the second computing device.

Abstract: A system and method utilize data buffers and data access schedules to improve handling of captured image data of an object under inspection for tomosynthetically processing such captured image data to reconstruct desired cross-sectional images therefrom. One embodiment implements a data buffer communicatively coupled to a radiographic imaging system that allows for storage of captured radiographic image data for at least a portion of multiple different projections of an object under inspection, such as image data associated with one or more angles of view of one or more different regions of the object, and then later that stored data may be used for tomosynthetically reconstructing cross-sectional images for the object under inspection.

Abstract: A system and method for computing histograms with exponential spacing of bins translates a fixed-point data sample that is to be placed in a bin to a floating-point representation (assuming the original data sample is not already in that particular format), estimates the base-2 logarithm of the floating-point representation, calculates an approximate histogram bin number based on the base-2 logarithm, and then adjusts the approximate bin number based on a comparison between the data sample and a data value associated with the approximate bin number.