Abstract: A method of identifying at least one particular person of interest in a collection of digital images taken over time, includes providing the collection of digital images with each digital image containing one or more persons; storing in a digital database an appearance model having a set of features that are distance measurements associated with facial features of the particular person of interest at an associated time; and providing an individual recognition classifier that uses the appearance model and the associated time to identify the particular person of interest in images from the collection of digital images.

Abstract: In an image enhancement method, a regular enhancement function and an aggressiveness parameter are computed using characteristics of a digital image. A first, relatively slow enhancement algorithm is applied to the digital image using the regular enhancement function, when an aggressiveness parameter is in a predetermined high range. A second, relatively fast enhancement algorithm is applied to the digital image using the regular enhancement function, when an aggressiveness parameter is in a predetermined low range. A modified enhancement function is calculated using characteristics of the digital image and is used with a second, relatively fast enhancement algorithm, when the aggressiveness parameter is in a predetermined medium range.

Abstract: A method for producing a distance map of scene distance values for a digital image captured by a digital camera includes capturing a first digital image of a scene under a first illumination condition, wherein the first digital image includes a plurality of pixels and the scene includes a plurality of scene objects located at different distances from the digital camera, capturing a second digital image of the scene under a second illumination condition that is different from the first illumination condition, and using the first and second digital images to produce a distance map having a plurality of scene distance values, wherein each scene distance value relates to the distance between the digital camera and the corresponding scene object.

Abstract: A method of processing a digital image captured by a camera includes providing an ambient air measuring device associated with the camera; using the ambient air measuring device to measure air attributes at substantially the time the digital image was captured; determining a transform for modifying the digital image from the measured air attributes; and applying the transform to the digital image to produce an improved digital image.

Abstract: In an eye detection method, a plurality of candidate eyes are located within a digital image. Pixels of interest having a predetermined characteristic and a predetermined association to respective eyes are found. Pixels of interest associated with each eye are grouped. Parametric boundaries are fit on each of the groups to define a plurality of detected eye features. The boundaries have a predefined uniform shape and a size matched to a respective group. Each of the detected eye features is scored as to a geometric relationship between the respective boundary and pixels of interest associated with the respective eye to provide eye feature scores.

Abstract: A method of processing a digital image to produce an improved digital image, includes receiving the digital image captured with a camera; determining a first vanishing point associated with the digital image; determining a second vanishing point associated with the digital image corresponding to a direction orthogonal the first vanishing point; determining a transform for modifying the digital image based on the first vanishing point and the second vanishing point; and applying the transform to the digital image to produce an improved digital image.

Abstract: A method of processing a digital image to produce an improved digital image, includes receiving the digital image captured with a camera; providing a gravity detection device integral with the camera; using the gravity detection device to determine the direction of gravity relative to the coordinate system of the camera at substantially the time the digital image was captured; determining a transform for modifying the digital image from the direction of gravity; and applying the transform to the digital image to produce an improved digital image.

Abstract: The age class of a human subject is ascertained in a digital image. The subject has a redeye defect pair; each defect having one or more defect pixels. In the method, two regions of pixels corresponding to the defects are identified. The distance between the regions is measured. A region size is determined, based upon the size of at least one of the regions. An age class is determined from the distance and region size.

Abstract: A method of improving a digital color image having pixels, the method includes identifying pixels from the digital color image representing one or more sky regions; detecting sky occlusion regions by examining the sky regions; developing a model based on the identified sky pixels, wherein such model is a mathematical function that has inputs of pixel position and outputs of color; and using the model to operate on the digital color image to replace the values of pixels from the sky occlusion regions with values predicted by the model.

Abstract: A method of detecting and correcting camera rotation in a digital camera, that includes the steps of: capturing a digital image to provide a captured digital image; and analyzing the captured digital image to detect a set of lines. The set of lines are used to determine a rotation angle of the captured digital image; and the captured digital image is modified based on the rotation angle, before storing the modified digital image.

Abstract: In a method and system for correcting redeye in a digital image of a human, a defect pair separation is measured. The members of the defect pair are each redeye defects in the image. Each defect has one or more pixels. The defects are adjusted, that is, retained unchanged or reduced in size to provide adjusted defects. The adjustment can follow growth of initial seed defects. The adjustment is responsive to the defect pair separation and can include trimming of pixels beyond a size limit calculated using the defect pair separation. Following the adjustment, the color of the adjusted defects is changed to reduce redeye.

Abstract: A method for reconstructing an extended color gamut digital image from a limited color gamut digital image includes transforming the limited color gamut digital image in the particular limited color gamut color space to a reference color space forming a limited color gamut digital image in a reference color space; providing a modified inverse color adjustment function which, when such function operates on the limited color gamut digital image in the reference color space, produces the reconstructed extended color gamut digital image having reduced highlight color saturation for highlight color values when compared with corresponding color values of the initial extended color gamut image; and operating on the limited color gamut digital image in the reference color space with the modified inverse color adjustment function to form the reconstructed extended color gamut digital image having reduced levels of color contouring and quantization artifacts.

Abstract: A method is described for applying an image enhancement algorithm to input digital images represented in different input color spaces including identifying the input color space of an input digital image, and applying a color space transformation to the input digital image represented in the input color space to form a corresponding input digital image in a reference color space. The method also includes adjusting one or more algorithm parameters of the image enhancement algorithm in response to the identified input color space, and applying the image enhancement algorithm with the one or more adjusted algorithm parameters to the corresponding input digital image in the reference color space to produce an enhanced digital image in the reference color space.

Abstract: A method for analyzing a digital image channel comprising the steps of providing a digital image channel, extracting a signal from the digital image channel, and using the extracted signal to determine whether the digital image channel is an interpolated digital image channel or a non-interpolated digital image channel. More specifically, the extracted signal comprises a signal related to differences between the values of neighboring pixels of the digital image channel, and the periodicity of the extracted signal is analyzed by computing a Fourier Transform signal of the extracted signal and looking for peaks in the Fourier Transform signal.

Abstract: A method of detecting sky in a digital color image having pixels is disclosed. The method includes identifying pixels from the digital color image representing an initial sky region; developing a model based on the identified sky pixels, wherein such model is a mathematical function that has inputs of pixel position and outputs of color; and using the model to operate on the digital color image to classify additional pixels not included in the initial sky region as sky.

Abstract: In processing a digital image to provide a desired grain appearance, a noise table is formed that represents noise magnitude vs. intensity of the image. A plurality of potential image processing paths are provided. Each path has one or more image transforms. The noise table is modified according to the image transforms in the respective image processing paths to provide a plurality of output noise tables. Noise metrics are generated from each of the output noise tables. The noise metrics each represent the appearance of the image processed by the respective image processing path. An input is then accepted designating one of the paths. The image is processed according to the designated image processing path to provide an output image having desired noise.

Abstract: A method of processing a digital image having pixels to improve the sharpness of a print generated from the digital image including determining a magnification value representing the magnification of a pixel of the digital image on the print based on the number of input digital image pixels and the output number of digital image pixels; producing a filter in response to the magnification value; using the filter to operate on the digital image to adjust the sharpness of the digital image to produce a sharpened digital image; resizing according to the magnification value the sharpened digital image to produce a resized sharpened digital image which includes the output number of digital image pixels; and producing the print based on the resized sharpened digital image.

Abstract: A method of applying a tone scale function that is compressive, expansive or a combination of both to a digital image, the method including decomposing the tone scale function into two or more composite functions that can be applied sequentially to the digital image; applying the first composite function to the digital image with a tone scale applicator to produce a tone scaled digital image; and applying the second composite function to the tone scaled digital image to produced an enhanced digital image.

Abstract: An image sensor generates an image signal with a differential response to image light. The image sensor has an array of photosites divided into standard photosites and non-standard photosites. A limiter provides the standard photosites with a predetermined standard response to a light exposure and the non-standard photosites with a predetermined slower response to the same light exposure. The standard photosites and nonstandard photosites both sparsely sample the array in a predetermined pattern.

Abstract: A digital image processing method for reducing the noise of a color digital image having pixel values, includes the steps of: identifying one or more color regions in color space; identifying a pixel of interest in the color digital image; calculating a color weighting factor for the pixel of interest; using the color weighting factor and the values of pixels sampled from a local neighborhood of pixels about the pixel of interest to calculate a noise reduced pixel value; replacing the original value of the pixel of interest with the noise reduced pixel value; and repeating the steps for other pixels in the digital image.