Abstract: Whether purple fringing (PF) has occurred is determined for every pixel of interest P(i,j) (step 41). The RGB ratio of a purple-fringed pixel P(i,j) at which PF has been determined and the RGB ratio of a PF convergence pixel P(m,n) spaced N pixels away from the purple-fringed pixel P(i,j) within a zone in the proximity of the purple-fringed pixel P(i,j) are calculated (steps 42, 43). A correction coefficient Rev (i,j) that causes the RGB ratio of the purple-fringed pixel P(i,j) to approach the RGB ratio of the PF convergence pixel P(m,n) is calculated (step 44). The purple-fringed pixel P(i,j) is color-corrected using the correction coefficient Rev (i,j) calculated. Purple fringing is made inconspicuous by changing the color of image portions at which purple fringing has occurred.

Abstract: A method for estimating the white Gaussian noise level that corrupts a digital image by discriminating homogeneous blocks from blocks containing a textured area and skipping these last blocks when evaluating the noise standard deviation.

Abstract: Various embodiments of the present invention are directed to methods and systems for processing signals, particularly signals encoding two-dimensional images, such as photographs, video frames, graphics, and other visually displayed information. In various method embodiments of the present invention, an input image signal is decomposed into an upper-envelope function, a lower-envelope function, and a details function. One or both of the upper-envelope and lower-envelope functions are then modified to produce one or more image-enhancing effects when the modified upper-envelope and lower-envelope functions are recombined with the details function to produce an enhanced image signal.

Abstract: Provided is an apparatus and method for detecting an image enhanced from a low resolution image to a high resolution image. An apparatus detects an image converted from a first resolution to a higher second resolution. A frequency converter converts a received second resolution image signal to a frequency domain. An image determiner calculates energy per frequency from the received second resolution image signal. If an amount of energy in over a pre-set frequency is less than a threshold, the received second resolution image signal corresponds to a second resolution image converted from a first resolution image, and if the amount of energy in over the pre-set frequency is greater than the threshold, determining that the received second resolution image signal corresponds to a real second resolution image.

Abstract: Embodiments of the present invention comprise methods and systems for signaling tone map data to an image recipient.

Abstract: The present invention relates to a method and an apparatus for reducing motion blur in a video signal. The apparatus comprises motion estimation means (1) for providing motion information of a video signal, high pass filter means (3a, 3b) for high pass filtering said video signal, and first modulating means (4a, 4b) for modulating the high pass filtered video signal from said high pass filter means (3a, 3b) with motion information from said motion estimation means (1) and for outputting a motion dependent high pass filtered video signal.

Abstract: An image processing apparatus including: an information amount calculation unit which reduces an image signal obtained by a CCD, and which performs a plurality of tone conversion processes of different characteristics on the reduced image signal to calculate an information amount of the image signal and an information amount of noise; a setting unit which formulizes the relationship of the information amount of the image signal and the information amount of the noise with respect to a tone conversion characteristic on the basis of the information amounts calculated by the information amount calculation unit, and which sets a tone conversion curve maximizing an effective information amount as a tone conversion curve used in the tone conversion processing; and a tone conversion unit which performs the tone conversion processing on the image signal on the basis of the tone conversion curve set by the setting unit.

Abstract: A filter circuit includes: an adder/subtractor that performs at least addition; and a shifter that performs multiplication/division by a power of two through a shift operation. The adder/subtractors and the shifter are configured to obtain a first calculation result representing a pixel value of a target pixel included in image data multiplied by a first filter coefficient. At least the adder/subtractors and the shifter is configured to obtain a second calculation result representing pixel values of a plurality of peripheral pixels adjacent to the target pixel, with each of the pixel values being multiplied by a second filter coefficient. The adder/subtractor is configured obtain a third calculation result by adding the first and second calculation results. The shifter configured to divide the third calculation result by a power of two which is equivalent to a sum of the first and second filter coefficients, so as to output the division result.

Abstract: An image processing apparatus comprises a first and a second eyes-and-mouth detecting units, a first and a second skin model generating units, an inside-of-mouth model generating unit, an eyeball model generating unit, a first and a second deformation parameter generating units, and an output unit. The first and second eyes-and-mouth detecting units detect eye boundaries and a mouth boundary from a first and a second face images, respectively. The first and second skin model generating units generate a first and a second skin models, respectively. The inside-of-mouth model generating unit and the eyeball model generating unit generate an inside-of-mouth model and an eyeball model, respectively. The first and second deformation parameter generating units generate a first and a second deformation parameters, respectively. The output unit output the first and second skin models, the first and second deformation parameters, the inside-of-mouth model, and the eyeball model as animation data.

Abstract: A method and a system for tracking the motion of moving objects accurately on the entirety of a wide-angle video is disclosed. The method includes using a non-uniform scaling to selectively enhance pixel density, preferably in preparation for other image processing. In preferred embodiments, the further image processing (such as motion detection, object recognition, or tracking, etc.) functions better with the enhanced pixel density or distribution.

Abstract: A method and system for structure enhancement and noise reduction of medical images using adaptive filtering is disclosed. The method utilizes feature estimation methods to determine multiple feature values for each pixel in an input image. Each pixel is then filtered using a filter type selected based on the feature values for that pixel.

Abstract: Imaging apparatus (20, 44) includes an array (22) of optical sensing elements (24), characterized by a pitch, which is adapted to generate a signal in response to optical radiation that is incident on the elements. Objective optics (26, 46), which have an optical axis (134) and are characterized by a cylindrical symmetry about the axis, are arranged to focus the optical radiation from an object onto the array with a point spread function (PSF) having an extent greater than twice the pitch of the array at an optimal focus of the objective optics.

Abstract: Which types of subject among a predetermined plurality of types of subject are contained in an image represented by input image data are detected. Features regarding the detected subject types are calculated in a feature calculating circuit based upon the image data. In accordance with the features calculated, the gain for every subject type is calculated. The gains are weighted and averaged using degrees of importance that have been input for every subject type. The input image data is corrected based upon applicable gains obtained by the weighted averaging.

Abstract: An image data processing method is provided. In this method, a plurality of original pixel values of an image is input. An interpolation position of a target pixel in the image is determined. Whether the interpolation position is in a central region of an object or in a marginal region of an object is determined. A pixel value interpolation with respect to the interpolation position is performed. When the interpolation position is in the central region of an object, the pixel value interpolation is performed in a first calculation mode, and when the interpolation position is in the marginal region of an object, the pixel value interpolation is performed in a second calculation mode, wherein the first calculation mode may be a low pass filtering interpolation mode, and the second calculation mode may be a linear interpolation mode.

Abstract: A distorted aberration correction processing apparatus includes DRAM and SRAM for storing an object image from an optical system. Further, the distorted aberration correction processing apparatus includes: a first address control circuit for reading out a pixel in the DRAM on a unit basis of an area including a plurality of the pixels along a curve corresponding to a distorted aberration of an optical system and writing the read-out pixel in SRAM; and a second address control circuit for reading out a pixel in the SRAM on a pixel basis and outputting the pixel read out on a pixel basis to an output portion so as to suppress the distorted aberration of the optical system. The first address control circuit effects control so that the signal of the areas is sequentially read out in a predetermined order, and the second address control circuit effects random access control.

Abstract: A method for processing remotely acquired imagery includes obtaining imagery data defining a first image of a panchromatic image type, the first image having a first spatial resolution, and obtaining imagery data defining a second image of a multi-spectral image type, the second image having a second spatial resolution lower than the first spatial resolution. The method also includes obtaining a mapping function specifying a position of pixels in the first image with respect to pixels in the second image and adapting the mapping function to a high common spatial resolution higher than the second spatial resolution. The method further includes generating a third set of imagery data defining a third image of a panchromatic type based on the first set of imagery data and the adapted mapping function and having the high common spatial resolution and adjusting the mapping function based on a first difference between the first and the third images at the high common spatial resolution.

Abstract: A computer-implemented method for image adaptation includes accepting a digitally-represented input image and a target size requirement. The input image is modified by optimally determining at least one of a resolution of the input image and a quality of the input image, the quality defining an amount of information allocated to represent each pixel value of the input image, so as to produce a compressed output image meeting the target size requirement.

Abstract: The formation of marks on devices is described. In one embodiment, a method for marking a device includes forming a plurality of unique marks sequentially on a device. The method includes defining a virtual array having a plurality of cells extending in an x-direction and a plurality of cells extending in a y-direction, wherein the marks are each positioned in a cell in the virtual array. The method also includes capturing an image including the relative cell position of the marks within the virtual array and converting the relative position of the marks within the virtual array into a set of coordinates including an x value along the x-direction and a y value along the y-direction for each of the marks. The method also includes generating a device identification using a plurality of the x values and the y values. Other embodiments are described and claimed.

Abstract: A pixel interpolation method for interpolating pixel values of a plurality of target positions of a target picture is disclosed. The pixel interpolation method includes: dynamically setting a plurality of edge detection ranges corresponding to the plurality of target positions, respectively; and for each of the plurality of target positions, performing a edge detection according to a corresponding edge detection range to determine an edge direction for the target position, and interpolating a pixel value for the target position according to pixel data corresponding to the edge direction.

Abstract: One embodiment is a method for suppressing background inaccuracies in binary to grayscale image conversion. A binary image is converted to a grayscale image using a neighbor map. An image enhancement function is applied to the grayscale image to suppress background inaccuracies in the grayscale image. Another embodiment is method for converting a binary pixel of a binary image to a grayscale pixel of a grayscale image and suppressing noise in the grayscale image using selective filtering of the binary image. Another embodiment is a method for converting a binary image to a first grayscale image and suppressing noise in the first grayscale image to produce a noise suppressed grayscale image using selective filtering of the first grayscale image.