Abstract: Embodiments provide a unified method for combining images such as high dynamic range images, flash-no-flash image pairs, and/or other images. Weight masks are defined for each of the plurality of images by calculating coefficients for each of the weight masks. Calculating the coefficients includes, at least, performing histogram alignment between a reference image and each of the other input images and by applying a mismatch bias to the coefficients as a function of the histogram alignment. After applying the weight masks to the corresponding images, the images are combined to produce a final image.

Abstract: Embodiments provide a unified method for combining images such as high dynamic range images, flash-no-flash image pairs, and/or other images. Weight masks are defined for each of the plurality of images by calculating coefficients for each of the weight masks. Calculating the coefficients includes, at least, performing histogram alignment between a reference image and each of the other input images and by applying a mismatch bias to the coefficients as a function of the histogram alignment. After applying the weight masks to the corresponding images, the images are combined to produce a final image.

Abstract: Embodiments provide a unified method for combining images such as high dynamic range images, flash-no-flash image pairs, and/or other images. Weight masks are defined for each of the plurality of images by calculating coefficients for each of the weight masks. Calculating the coefficients includes, at least, performing histogram alignment between a reference image and each of the other input images and by applying a mismatch bias to the coefficients as a function of the histogram alignment. After applying the weight masks to the corresponding images, the images are combined to produce a final image.

Abstract: Embodiments provide a unified method for combining images such as high dynamic range images, flash-no-flash image pairs, and/or other images. Weight masks are defined for each of the plurality of images by calculating coefficients for each of the weight masks. Calculating the coefficients includes, at least, performing histogram alignment between a reference image and each of the other input images and by applying a mismatch bias to the coefficients as a function of the histogram alignment. After applying the weight masks to the corresponding images, the images are combined to produce a final image.

Abstract: A simulation demonstrating or teaching a procedure used in a software program based on a script of commands that are executed by a script engine. The script engine interprets the commands using libraries of functions that interact with the software program and the operating system of the computer on which the script engine is executed. The commands are control actions implemented within the software to emulate the actions of an expert carrying out the procedure being simulated. For example, the commands cause a mouse cursor to select a specified item from a drop down menu list as if the cursor were being controlled by the expert in an appropriate display screen of the software program. A plurality of images are thus created showing the cursor in different positions as it moves on the display screen. Text is entered in response to the commands, causing images showing each letter (or phrase) being entered, as if by the expert.