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: 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 associated with the particular person of interest and a prior probability of the person of interest appearing in images by a particular photographer; and comparing the appearance model with features extracted from the digital images in the collection of digital images and using the prior probability and the appearance model to determine if the particular person of interest is in one or more digital images in the collection of digital images.

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 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: An electronic camera for producing an output image of a scene from a captured image signal includes a first imaging stage comprising a first image sensor for generating a first sensor output and a first lens for forming a first image of the scene on the first image sensor, and a second imaging stage comprising a second image sensor for generating a second sensor output and a second lens for forming a second image of the scene on the second image sensor, where the lenses have different focal lengths. A processing stage uses the sensor output from one of the imaging stages as the captured image signal and uses the images from both imaging stages to generate a range map identifying distances to the different portions of the scene.

Abstract: A method is disclosed for retrieving images relevant to an example image from among a plurality of stored images, each of the stored images being associated with metadata of different types, including retrieving set(s) of images from the stored image(s) for each different type of metadata that are based on similarities of the metadata of each different type with the example image; displaying the retrieved set(s) of image(s) organized according to each different type of metadata; and the user selecting one or more particular set(s) of retrieved image(s).

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 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 organizing an image collection includes detecting faces in the image collection, extracting features from the detected faces, determining a set of unique faces by analyzing the extracted features, wherein each face in the set of unique faces is believed to be from a different person than the other faces in the set; and displaying the unique faces to a user.

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 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 is described for detecting the clipped pixels of a digital color image. The method includes the steps of: (a) producing a uniformity map from the digital color image, where the uniformity map indicates locations within the digital color image that are substantially uniform; (b) providing a threshold value; and (c) using the uniformity map, the threshold value, and the digital color image to produce a map indicating the location of clipped pixels within the digital color image.

Abstract: In order to reduce image degradation due to image capture problems, a method utilizes image data corresponding to a captured image and image capture metadata that refers specifically to information that is associated with capture of the image. A database of correction parameters is provided in order to reduce degradation present in the captured image, whereby each correction parameter is associated with particular image capture metadata. The method involves using the image capture metadata to determine whether the database contains one or more correction parameters associated with that image capture metadata, and then producing correction parameters from the database of correction parameters when the database contains correction parameters associated with the image capture metadata. One or more new correction parameters are produced when the database does not contain correction parameters associated with the image capture metadata. The database then may be updated with the new correction parameters.

Abstract: A method of identifying a particular background feature in a digital image, and using such feature to identify images in a collection of digital images that are of interest, includes using the digital image for determining one or more background region(s), with the rest of the image region being the non-background region; analyzing the background region(s) to determine one or more features which are suitable for searching the collection; and using the one or more features to search the collection and identifying those digital images in the collection that have the one or more features.

Abstract: A method of classifying regions in a digital image or video captured by an image capture device includes providing a geographic location determining device associated with the image capture device; using the location determining device to measure the image capture location at substantially the time that the digital image or video was captured; and classifying regions in the captured digital image or video into one or more classes based on the image-capture location.

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: The present disclosure relates to automatically generating a dynamic set of metadata from digitized hardcopy media. The technique includes scanning the image side and non-image side of a plurality of hardcopy media. A dynamic digital metadata record of each of the plurality of hardcopy media is created and used for manipulating each of the plurality of hardcopy media.

Abstract: A method of processing a color digital image having a luminance channel and one or more chrominance channels to improve the tone scale characteristics of the image, includes the steps of: producing a control signal from the one or more chrominance channels; generating a pedestal signal containing mainly low frequency modulation by filtering the luminance channel with a spatial filter, whereby the operation of the spatial filter is modulated by the control signal; and producing a texture signal by subtracting the pedestal signal from the luminance channel.

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.