Abstract: Systems and method of generating compound images having increased sharpness and reduced noise are described. In one aspect, a comparison image signal is determined. The comparison image signal includes pixels with values respectively indexing values of pixels of a first image signal in relation to values of spatially corresponding pixels of a second image signal. The comparison image signal is filtered with a spatial filter. A compound image signal is generated. The compound image signal has pixels with values composed of contributions from the pixel values of the first image signal and the pixel values of the second image signal. The contributions are functions of respective values of spatially corresponding pixels in the filtered comparison image signal in relation to values of noise variation in the filtered comparison image signal.

Abstract: Peteye is the appearance of an unnatural coloration (not necessarily red) of the pupils in an animal appearing in an image captured by a camera with flash illumination. Systems and methods of detecting and correcting peteye are described. In one aspect a classification map segmenting pixels in the input image into peteye pixels and non-peteye pixels is generated based on a respective segmentation condition on values of the pixels. Candidate peteye pixel areas are identified in the classification map. The generating and the identifying processes are repeated with the respective condition replaced by a different respective segmentation condition on the pixel values.

Abstract: In a method of processing an input image, compression parameters of the input image are determined and luminance artifacts in the input image are reduced to obtain an improved luminance component of the input image, where the determined compression parameters guide the luminance artifact reduction. In addition, a chrominance noise and chrominance artifact level of the input image is estimated and a spatially-correlated chrominance noise and chrominance artifact of the input image is reduced with the improved luminance component, where the estimated chrominance noise and chrominance artifact level guide the spatially-correlated chrominance noise and chrominance artifact reduction to obtain an improved chrominance component of the input image. Moreover, an output image having the improved luminance component and the improved chrominance component is outputted.

Abstract: The present invention provides methods, systems and a machine readable medium including machine readable code for identifying an ill-exposed image. An image including a first image block is received. The luminance data and the texture energy data associated with the first image block are assessed. A determination is made regarding whether the received image is an ill-exposed image based on the assessment of the luminance data and the assessment of the texture energy data associated with the first image block.

Abstract: A method for determining an indication of how well-focused an image is. An image is divided into a plurality of blocks. At least one local measure is determined for at least one block of the plurality of blocks. At least one global figure-of-merit is determined for the image based on the local measure. An indication of focus is determined based on the global figure-of-merit.

Abstract: Representations of an input signal at different lower resolutions are obtained, where n denotes a level of resolution, and where 0?n?N. Level n=N corresponds to the representation having the lowest resolution, and level n=0 corresponds to the input signal. The resolution increases as level n decreases. The nth level representation is used to estimate and remove low frequency error in the n?1th level representation. Then application-specific processing is performed on the n?1th level representation.

Abstract: Peteye is the appearance of an unnatural coloration (not necessarily red) of the pupils in an animal appearing in an image captured by a camera with flash illumination. Systems and methods of detecting and correcting peteye are described. In one aspect a classification map segmenting pixels in the input image into peteye pixels and non-peteye pixels is generated based on a respective segmentation condition on values of the pixels. Candidate peteye pixel areas are identified in the classification map. The generating and the identifying processes are repeated with the respective condition replaced by a different respective segmentation condition on the pixel values.

Abstract: A method, apparatus, and system are disclosed for selecting quality images from multiple captured images. One embodiment is an image capturing system. The system includes hardware for capturing a plurality of consecutive images and a processor for determining a quality indication for the consecutive images and for selecting one of the consecutive images based on the quality indication.

Abstract: An image processing method and device are described. The method includes the steps of capturing the contents a scene in a first pass (310), determining a binning pattern for pixels representing the scene (350) based on measured brightness values of the pixels (320) and capturing contents of the image in a second pass using the binning pattern (360).

Abstract: A method and system for deblurring an image based on motion tracking. light is recorded at an image sensor of an imaging device to capture an image. motion of said image sensor is recorded at a motion sensor of the imaging device during the recording of the light at the image sensor. A blur kernel is generated based on the motion.

Abstract: Processing of a digital image includes applying a function to a plurality of pixels in the image, the function relating a noise statistic to pixel intensity values. By applying the noise statistic function, a noise statistic value is produced for each of the pixels. Each of the pixels is processed with respect to its noise statistic value.

Abstract: Methods, machines, and machine-readable media for processing multiple exposure source images, including a reference image and one or more non-reference images, are described. In one aspect, respective sets of motion vectors that establish correspondences between respective pairs of the source images are calculated. Ones of the source images are warped to a reference coordinate system based on the sets of motion vectors. For each of the non-reference ones of the warped images, a respective set of one or more measures of alignment confidence between the non-reference warped image and the reference image in the reference coordinate system is computed. Saturated pixels and unsaturated pixels are identified in the warped images. An output image with pixel value contributions from unsaturated pixels in the warped images is generated based on the computed alignment confidence measures.

Abstract: A method performed by a processing system is provided. The method comprises computing an auto-correlation of sharp channel information of a digital image, computing a cross-correlation between the sharp channel information and blurred channel information of the digital image, and estimating a blur kernel using the auto-correlation and the cross-correlation.

Abstract: Denoising of a plurality of pixels of a color digital image includes analyzing the plurality of pixels to identify those pixels having a high likelihood of containing significant noise; and forcing those pixels having a high likelihood of containing significant noise to be photometrically coherent with nearby pixels having a lower likelihood of containing significant noise.

Abstract: Embodiments of the present invention employ robust filtering at each of a number of scales, or resolutions, within a signal, such as a still image or video sequence. In certain embodiments of the present invention, robust filtering comprises or includes a non-linear neighborhood operation at each scale in order to produce both a denoised, sharpened and contrast-enhanced signal and a correction signal at each scale. Correction signals and sharpened and contrast-enhanced signals are combined to produce a denoised, sharpened and contrast-enhanced output signal. Scale-appropriate enhancements at each scale or resolution, including denoising, sharpening and contrast enhancement, ameliorate artifacts introduced by re-enhancement, at a second scale or resolution, features previously enhanced at another scale or resolution and inhibit over enhancement.

Abstract: Embodiments of the present invention employ robust filtering at each of a number of scales, or resolutions, within a signal, such as a still image or video sequence. In certain embodiments of the present invention, robust filtering comprises or includes a non-linear neighborhood operation at each scale in order to produce both a denoised, sharpened and contrast-enhanced signal and a correction signal at each scale. Correction signals and sharpened and contrast-enhanced signals are combined to produce a denoised, sharpened and contrast-enhanced output signal. Scale-appropriate enhancements at each scale or resolution, including denoising, sharpening and contrast enhancement, ameliorate artifacts introduced by re-enhancement, at a second scale or resolution, features previously enhanced at another scale or resolution and inhibit over enhancement.

Abstract: A method of calibrating a camera includes capturing a set of dark images at each of a plurality of different exposure settings, thereby generating a plurality of sets of dark images. Each set of dark images is averaged, thereby generating a fixed pattern noise image corresponding to each one of the exposure settings. The method includes determining fixed pattern noise for at least one pixel of the camera based on an exposure setting of the camera and at least one of the fixed pattern noise images.

Abstract: Systems and method of generating compound images having increased sharpness and reduced noise are described. In one aspect, a comparison image signal is determined. The comparison image signal includes pixels with values respectively indexing values of pixels of a first image signal in relation to values of spatially corresponding pixels of a second image signal. The comparison image signal is filtered with a spatial filter. A compound image signal is generated. The compound image signal has pixels with values composed of contributions from the pixel values of the first image signal and the pixel values of the second image signal. The contributions are functions of respective values of spatially corresponding pixels in the filtered comparison image signal in relation to values of noise variation in the filtered comparison image signal.

Abstract: A computer method for transforming a sensor color space of a digital image to standard color space. The color pixels in the sensor color space digital image are grouped and multiplied by multiple color conversion matrices without amplifying sensor noise. Different color conversion matrices are used for different parts of the image. The sum of the color error and amplified noise is minimized.

Abstract: Methods, systems, and machine-readable media for processing an input image are described. In one aspect, respective visual features of local input image regions of an input image having a first pixel resolution are analyzed to produce a result. Based on the result of analyzing the visual features, reduced-resolution visual representations of corresponding ones of the local input image regions are derived from the input image. A thumbnail image that reflects the arrangements, proportions and local details of the input image having a second pixel resolution lower than the first pixel resolution is produced from the reduced-resolution visual representations. The thumbnail image is output.