Abstract: A method of processing a digital image, including the steps of: assigning belief values to pixels in the digital image, wherein the belief values are proportional to a belief that the pixels are associated with human skin; calculating a brightness adjustment amount based on a statistic of the pixels with belief values exceeding a threshold and the assigned belief values of the pixels; and applying the brightness adjustment amount to the digital image to produce a processed digital image having improved overall brightness.

Abstract: A method of transforming the color appearance of a plurality of digital images includes receiving a plurality of digital images from a capture medium wherein each digital image includes a plurality of pixel values relating to at least three basic colors; calculating a color correction transform by using a non-linear adjustment that is independent of the digital images and which corrects an under-exposure condition as a function of the capture medium; and a linear functional relationship dependent upon the pixels of the basic colors, the linear functional relationship defining an exposure-level-dependent estimate of gray corresponding to the photographic response of the capture medium; and using the color correction transform to modify the pixels of the plurality of digital images wherein the pixels within a digital image are transformed with varying degrees of color modification as a function of exposure.

Abstract: A method of processing a digital image, including the steps of applying an initial scene balance algorithm to the digital image to produce an initial scene balanced digital image; detecting skin colored pixels in the initial scene balanced digital image, calculating a brightness adjustment amount based on a statistic of the detected skin colored pixels; and applying the brightness adjustment amount to the scene balanced digital image to produce a processed digital image having improved overall brightness.

Abstract: A method of processing a digital image, including the steps of: assigning belief values to pixels in the digital image, wherein the belief values are proportional to a belief that the pixels are associated with human skin; calculating a brightness adjustment amount based on a statistic of the pixels with belief values exceeding a threshold and the assigned belief values of the pixels; and applying the brightness adjustment amount to the digital image to produce a processed digital image having improved overall brightness.

Abstract: A method of transforming the color appearance of a plurality of digital images includes receiving a plurality of digital images from a capture medium wherein each digital image includes a plurality of pixel values relating to at least three basic colors; calculating a color correction transform by using a non-linear adjustment that is independent of the digital images and which corrects an under-exposure condition as a function of the capture medium; and a linear functional relationship dependent upon the pixels of the basic colors, the linear functional relationship defining an exposure-level-dependent estimate of gray corresponding to the photographic response of the capture medium; and using the color correction transform to modify the pixels of the plurality of digital images wherein the pixels within a digital image are transformed with varying degrees of color modification as a function of exposure.

Abstract: A method of processing a digital image, including the steps of: applying an initial scene balance algorithm to the digital image to produce an initial scene balanced digital image; detecting skin colored pixels in the initial scene balanced digital image; calculating a brightness adjustment amount based on a statistic of the detected skin colored pixels; and applying the brightness adjustment amount to the scene balanced digital image to produce a processed digital image having improved overall brightness.

Abstract: The critical dimensions of product samples made during a standard certification procedure for an injection molding process are measured and a loss factor value is computed for each such dimension. Using statistical techniques, the largest loss factor value is partitioned into percentages of loss contributed by a predetermined set of loss elements. The loss element contributing the largest percentage is corrected so as to improve the quality of the process and the product. The method provides a way of determining what kinds of process corrections will most effectively improve product and process quality.