Abstract: A method comprising using at least one hardware processor for computing a patch distinctiveness score for each of multiple patches of a medical image, computing a shape distinctiveness score for each of multiple regions of the medical image, and computing a saliency map of the medical image, by combining the patch distinctiveness score and the shape distinctiveness score.

Abstract: A method for detecting a scratch on a printed image is disclosed, which may include obtaining a digital representation of the printed image and a digital reference image. The method may also include summing values of pixels of pixel lines in at least one segment of the digital representation of the printed image along a suspected direction to obtain a projection signal of the digital representation of the printed image for that segment, and summing values of pixels in a corresponding at least one segment of the digital reference image in the suspected direction to obtain a projection signal of the reference image for the corresponding segment. The method may further include comparing the projection signals to detect dissimilarity indicative of a directional coherence in the suspected direction due to a scratch in the segment of the digital representation of the printed image. Non-transitory computer readable medium and system are also disclosed.

Abstract: A method comprises computing an activity map for an input image. The activity map indicates an amount of variable spatial activity in the input image. The method further comprises producing an output image based on the activity map, and controlling a printhead to cause the output image to be printed. The output image contains a plurality of color pixels and each such color pixel is represented by at least one of cyan (C), magenta (M), yellow (Y), and black (K) in a color space.

Abstract: Machines, systems and methods for object relationship characterization are provided. The method comprises providing a plurality of images, each having a plurality of pixels; selecting a pair of images from the plurality of images, the pair of images comprises a first image and a second image; characterizing at least one pixel of the first image and the second image by a first feature vector and a second feature vector respectively; characterizing the first image by a first probability distribution over the first feature vector; characterizing the second image by a second probability distribution over the second feature vector; assigning a list of histogram bins for the first image and the second image; computing a distribution flow descriptor (DFlow) for capturing relationship between the first probability distribution and the second probability distribution.

Abstract: Indications are received regarding which of plural outputs are preferred over others of the plural outputs. A continuous function is computed that satisfies constraints corresponding to the received indications and that satisfies a predefined criterion. Values of parameters are computed based on the continuous function, wherein the values of the parameters are useable in a process to generate an output.

Abstract: A method comprises computing an activity map for an input image. The activity map indicates an amount of variable spatial activity in the input image. The method further comprises producing an output image based on the activity map, and controlling a printhead to cause the output image to be printed. The output image contains a plurality of color pixels and each such color pixel is represented by at least one of cyan (C), magenta (M), yellow (Y), and black (K) in a color space.

Abstract: In one respect, provided are systems, methods and techniques in which local regions within an image are processed to provide fuzzy classification scores, which are calculated by determining changes in pixel values along a number of different directions. The resulting fuzzy classification scores are then used to detect or identify edge-containing or texture-containing regions, or to otherwise process the image regions differentially according to their fuzzy classification score. In another respect, provided are systems, methods and techniques for differential processing of different areas in an image. The differential processing in this case is based on calculated measures of local activity, which indicate features in corresponding local regions, and also based on calculated measures of local pixel-value variations, which indicate an amount of variation in pixel values across the corresponding local regions.

Abstract: A method of detecting streaks in printed documents comprises, with an imaging device, capturing an image of a printed document, transmitting the image data representing the printed document to a computing device, with the computing device, dividing the image data into a number of rectangles horizontally across the image data so that the rectangles overlap in the horizontal direction, and with the computing device, determining if a rectangle comprises a streak. A system for detecting and evaluating streaks in printed document comprises a printing device that prints a document based on image data received from a computing device, an imaging device that captures an image of the printed document, and a streak detector that detects streaks within the captured image of the printed document.

Abstract: A method (10) can comprise detecting (40) a shadow for a reference object (356) in a target image (350) in response to user input marking the reference object (356). The method can also comprise forming (170) a shadow (652) for an insertion object (310) to be inserted into the target image (350) based on the detected shadow for the reference object (356). The method can further comprise inserting (180) the shadow (652) for the insertion object (31p) into the target image (350).

Abstract: A method for enhancing an input image to produce an enhanced output image is provided. The method includes constructing a photographic-mask intermediate image without low-contrast details and a temporary-image intermediate image with enhanced mid-contrast details, retained high-contrast details, and reduced low-contrast details, and employing values for the photographic-mask intermediate image and temporary-image intermediate image to produce the enhanced output image that is globally and locally contrast-enhanced, sharpened, and denoised.

Abstract: A method for detecting a scratch on a printed image is disclosed, which may include obtaining a digital representation of the printed image and a digital reference image. The method may also include summing values of pixels of pixel lines in at least one segment of the digital representation of the printed image along a suspected direction to obtain a projection signal of the digital representation of the printed image for that segment, and summing values of pixels in a corresponding at least one segment of the digital reference image in the suspected direction to obtain a projection signal of the reference image for the corresponding segment. The method may further include comparing the projection signals to detect dissimilarity indicative of a directional coherence in the suspected direction due to a scratch in the segment of the digital representation of the printed image. Non-transitory computer readable medium and system are also disclosed.

Abstract: A method of reducing blurring in an image of size greater than M columns by N rows of pixels, comprises deriving a blur kernel k representing the blur in the image, and deriving an inverse blur kernel k?1. The inverse blur kernel is given by (I) where h(m) is the sum of the first m terms of the series (II) ? is the Dirac delta, m is greater than 1, and h(m) is a two dimensional matrix of size M×N. The two dimensional matrix h(m) is convolved with the image over the whole image in the image pixel domain to produce an image with reduced blur. The method may be applied to a video sequence allowing the sequence of images to be deblurred in real time.

Abstract: Methods, machines, and computer-readable media for processing an input image with a bi-selective filter in a transform domain are described. In one aspect, a forward transform of an input image is computed. A bi-selective filter smoothes image regions with low magnitude coefficients and sharpens image regions with high magnitude coefficients. An output image is generated from the filtered forward transform.

Abstract: A technique includes using a processor-based machine to determine a discrete color flow transformation to map target colors of a target object to source colors of a source object based at least in part on a first histogram indicating a color distribution of the target object and a second histogram of a color distribution indicating the source object. The technique includes determining a continuous color flow transformation to map the target colors to the source colors based at least in part on the discrete color flow transformation; and transforming the target colors of the target object to generate a third object based at least in part on the continuous color flow transformation.

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: Indications are received regarding which of plural outputs are preferred over others of the plural outputs. A continuous function is computed that satisfies constraints corresponding to the received indications and that satisfies a predefined criterion. Values of parameters are computed based on the continuous function, wherein the values of the parameters are useable in a process to generate an output.

Abstract: A technique includes using a processor-based machine to determine a discrete color flow transformation to map target colors of a target object to source colors of a source object based at least in part on a first histogram indicating a color distribution of the target object and a second histogram of a color distribution indicating the source object. The technique includes determining a continuous color flow transformation to map the target colors to the source colors based at least in part on the discrete color flow transformation; and transforming the target colors of the target object to generate a third object based at least in part on the continuous color flow transformation.

Abstract: A method of detecting streaks in printed documents comprises, with an imaging device, capturing an image of a printed document, transmitting the image data representing the printed document to a computing device, with the computing device, dividing the image data into a number of rectangles horizontally across the image data so that the rectangles overlap in the horizontal direction, and with the computing device, determining if a rectangle comprises a streak. A system for detecting and evaluating streaks in printed document comprises a printing device that prints a document based on image data received from a computing device, an imaging device that captures an image of the printed document, and a streak detector that detects streaks within the captured image of the printed document.

Abstract: A set of local noise variation values characterizing local noise levels in the input image is calculated. Local contrast enhancement is performed on image forming element values derived from the input image to produce a contrast enhanced image. Values of local noise amplification caused by the local contrast enhancement are ascertained. Noise in the contrast enhanced image is reduced based on the set of local noise variation values and the local noise amplification values.

Abstract: A method of reducing blurring in an image of size greater than M columns by N rows of pixels, comprises deriving a blur kernel k representing the blur in the image, and deriving an inverse blur kernel k?1. The inverse blur kernel is given by (I) where h(m) is the sum of the first m terms of the series (II) ? is the Dirac delta, m is greater than 1, and h(m) is a two dimensional matrix of size M×N. The two dimensional matrix h(m) is convolved with the image over the whole image in the image pixel domain to produce an image with reduced blur. The method may be applied to a video sequence allowing the sequence of images to be deblurred in real time.