Abstract: Information associated with data which was previously transmitted to a client terminal (201 or 202) is recorded as a history. When a transmission request of data of logical units in tiles required to obtain a desired image is received from the client terminal (201), the type of progression order used in the client terminal (201) is discriminated with reference to the history. The transmission order of the data of the logical units in the tiles to be transmitted to the client terminal (201) is determined in accordance with the discrimination order, and the data of the logical units in the tiles are transmitted to the client terminal (201) in accordance with the determined transmission order.

Abstract: The image processing device is equipped with an image area extracting part for extracting a plurality of image areas from image data, an image positional information recognizing part for recognizing positional information of each extracted image area, an attribute recognizing part for recognizing at least attributes concerning whether each extracted image area is a filled closed area or unfilled closed area, a file producing part for producing a file synthesizing a plurality of image areas based on the positional information recognized by the image positional information recognizing part, and a sequence setting part for setting overlying sequence for each image area in accordance with the recognition result of the attribute recognizing part. The file producing part produces the file by overlaying a multiple of image areas in accordance with the overlaying sequence set up by the sequence setting part.

Abstract: The present symmetric stereo matching technique provides a method for iteratively estimating a minimum energy for occlusion and disparity using belief propagation. The minimum energy is based on an energy minimization framework in which a visibility constraint is embedded. By embedding the visibility constraint, the present symmetric stereo matching technique treats both images equally, instead of treating one as a reference image. The visibility constraint ensures that occlusion in one view and the disparity in another view are consistent.

Abstract: Systems and techniques for processing sequences of video images involve receiving, on a computer, data corresponding to a sequence of video images detected by an image sensor. The received data is processed using a graphics processor to adjust one or more visual characteristics of the video images corresponding to the received data. The received data can include video data defining pixel values and ancillary data relating to settings on the image sensor. The video data can be processed in accordance with ancillary data to adjust the visual characteristics, which can include filtering the images, blending images, and/or other processing operations.

Abstract: An apparatus comprising an edge detector circuit, an edge strength detector and an edge strength threshold circuit. The edge detector circuit may be configured to determine a plurality of default directions of a macroblock in response to a plurality of input signals comprising information about a plurality of samples in the macroblock. The edge strength detector circuit may be configured to generate a maximum strength signal and a next maximum strength signal in response to the default directions. The edge strength threshold circuit may be configured to generate an edge direction signal and an edge strength signal in response to the maximum strength signal and the next maximum strength signal. The edge direction signal may comprise (i) any one of the default directions when in a first state and (ii) any one of a plurality of intermediate directions when in a second state.

Abstract: In a method for reconstructing a 3D CT image from a number of 2D projection images each 2D projection image is divided at an arbitrarily selectable position by a substantially vertical image line and the projection image is automatically electronically analyzed to detect whether clipping occurs on the left side or on the right side, or on both sides, of the image line. For each side of the image line at which clipping is detected, a horizontal coordinate at which the clipping ends is identified. The grayscale values at the side of the horizontal coordinate opposite to the side at which the image line is located are extrapolated so that the clipping is removed. The corrected 2D projection images are then used to reconstruct a 3D image, in which capping artifacts, that would otherwise be present, or avoided or substantially minimized due to the corrections made in the 2D projections.

Abstract: A method for enhancing an image includes applying an auto-level transformation to an original image to form a first image, applying an auto-contrast transformation to the original image to form a second image, and applying an auto-brightness transformation to the original image to form a third image. The method further includes applying a color cast correction to the first, the second, and the third images to generate a first group of images, applying a gamma correction to the first group of images to generate a second group of images, applying a sharpening correction to the second group of images to generate a third group of images, and presenting the third group of images to a user to select a final result.

Abstract: An image is processed by a sensed-feature-based classifier to generate a list of objects assigned to classes. The most prominent objects (those objects whose classification is most likely reliable) are selected for range estimation and interpolation. Based on the range estimation and interpolation, the sensed features are converted to physical features for each object. Next, that subset of objects is then run through a physical-feature-based classifier that re-classifies the objects. Next, the objects and their range estimates are re-run through the processes of range estimation and interpolation, sensed-feature-to-physical-feature conversion, and physical-feature-based classification iteratively to continuously increase the reliability of the classification as well as the range estimation. The iterations are halted when the reliability reaches a predetermined confidence threshold.

Abstract: In a decoding method of decoding encoded image data which has been hierarchically encoded in advance, a size of an image to be outputted is determined, and then the encoded image data is decoded up to a layer of hierarchy which is at least one layer more than a minimum number of layer/layers of hierarchy necessary to acquire an image of the determined size.

Abstract: Provided is a background recovering apparatus for deleting an object of an arbitrary region and recovering a background covered with the object. The apparatus includes a storing block for storing the input image sequence, and storing the three dimensional (3D) position and posture information, and focal length information; a geometric information extracting block for extracting 3D with respect to the background; a background image generating block for generating the background image; and a background image inserting block for recovering the background by inserting the background image into an arbitrary region of a first view point.

Abstract: A method for evaluating an image of a predetermined extract of a printed product makes corrections to a white reference to account for spatial variations and changes of illumination intensity over time. Intensity signals recorded from first predetermined areas within the extract are combined arithmetically with reference data values that represent a measure of the intensity of the light reflection from unprinted regions of the printed product. At the start, an image of a white reference is recorded and basic reference data for the entire extract are derived from the intensity signals of this image. During each evaluation of an image of the predetermined extract, correction data are derived from intensity signals recorded from second predetermined areas within the extract.

Abstract: A method for automatically cropping image objects, including: an object contour detecting step, an image dividing step, and an image merging step. The object contour detecting step detects object contours with Modified Laplacian Contour Detector to generate a binary image. The image dividing step divides the binary image into a background region and a plurality of non-background regions with Connected Components Algorithm (CCA). The image merging step merges the closer non-background regions from large to small, and determines whether the merging is reasonable for cropping the image object.

Abstract: A sub-sampling portion (101) sub-samples images of data corresponding to the left and right viewpoints. A joining method selector (104) selects the joining method that minimizes the discontinuity at the boundary in the joined image when the sub-sampled images of data are joined. A joining portion (102) joins the plurality of images data, based on the selected joining method. An encoder (103) encodes the joined image data, and a joining method encoder (105) encodes the information of the joining method. A multiplexer (106) multiplexes these pieces of coded data. In this way, the continuity of the joined image is improved, whereby the coding efficiency is enhanced.

Abstract: The method/device reconstructs/represents multidimensional objects from one- or two-dimensional image data based on recordings of one- or two-dimensional partial image areas, wherein spatial/positions of individual partial image areas are used along with one- or two-dimensional image information of the individual partial image areas to generate one- or two-dimensional image data, wherein a first group of space elements is generated in a multidimensional voxel space from first space elements which contain multidimensional image information and touch/intersect planes or lines of partial image areas by means of the one- or two-dimensional image data, and wherein a second group of space elements is generated in the multidimensional voxel space from second space elements by means of information transformation from the multidimensional image information of the first group of space elements.

Abstract: The invention relates to a method and a system for digitally processing of frequently updated images from a camera. The system comprises at least one camera (2), at least one display unit, a network (6) for connecting the at least one camera with at least one display unit, and an image processing means (30). The image processing means comprises means for defining a first scaling area and a peripheral scaling area, which is enclosing the first scaling area, within an acquired digital image, and means for scaling the peripheral scaling area differently than the first scaling area so that the peripheral scaling area is downscaled in relation to the first scaling area, wherein the first scaling area is uniformly scaled in both a vertical and a horizontal direction.

Abstract: A method and program product for real-time correction of non-functioning pixels in digital radiography, where the method comprises: receiving a list of non-functioning pixels; determining which neighboring functioning pixels are needed to correct the non-functioning pixels; organizing those neighboring functioning pixels and corresponding non-functioning pixels into a plurality of groups by a number of pixels used to perform correction; and performing correction of data from non-functioning pixels within one of the plurality of groups and subsequently performing correction of data from non-functioning pixels within another one of the plurality of groups.

Abstract: A method of modulating a dynamic range of a plurality of picture elements each containing image information. The method comprises: (a) inputting the plurality of picture elements and extracting, from the image information of a picture element of the plurality of picture elements an intensity level being in a first dynamic range; and (b) for the picture element: (i) defining a surrounding region of picture elements and a remote region of picture elements; (ii) selecting at least one adaptation weight-function; and (iii) using the at least one adaptation weight-function and intensity levels of each picture element of the surrounding and the remote regions, for assigning a new intensity level to the picture element, the new intensity level being in a second dynamic range, thereby modulating the dynamic range of the plurality of picture elements.

Abstract: Compact and efficient hardware architectures for implementing lifting-based DWTs, including 1-D and 2-D versions of recursive and dual scan architectures. The 1-D recursive architecture exploits interdependencies among the wavelet coefficients by interleaving, on alternate clock cycles using the same datapath hardware, the calculation of higher order coefficients along with that of the first-stage coefficients. The resulting hardware utilization exceeds 90% in the typical case of a 5-stage 1-D DWT operating on 1024 samples. The 1-D dual scan architecture achieves 100% datapath hardware utilization by processing two independent data streams together using shared functional blocks. The 2-D recursive architecture is roughly 25% faster than conventional implementations, and it requires a buffer that stores only a few rows of the data array instead of a fixed fraction (typically 25% or more) of the entire array.

Abstract: An electronic correction system and method for correcting optical anomalies, namely distortions, color non-convergence (excluding axial chromatic aberration) and luminance (or chrominance) non-uniformity. Each effect is modeled as a transformation in either spatial (positional) space or color space. Representing the effects as transformations of digital pixel data, allows the different anomalies to be resolved within a common framework, namely that of image ‘warping’. The anomaly, having been expressed as a pixel transformation, is then eliminated by electronically applying the inverse transformation. This process is equivalent to digitally manipulating or warping the image in position and/or color space and accordingly this can be achieved using commercially known warping circuits. In addition, the transformation can also contain a component to additionally perform any application specific image warping (e.g. scaling and geometric transformations).

Abstract: An apparatus for recognizing characters includes a text structure analyzing unit that analyzes an input image of text composed of mixed typed and handwritten characters and separates the input text image into predefined text imaging regions, a character clipping unit that clips characters one by one in each of the text imaging regions separated by the text structure analyzing unit, a feature vectors calculating unit that calculates feature vectors of the clipped characters for each of the text imaging regions, a feature vectors aggregating unit that aggregates the calculated feature vectors over a predefined range of the input text image, and a typed and handwritten character separation unit that separates characters involved in the input text image into the typed characters and the handwritten characters, based on a result of the aggregation by the feature vectors aggregating unit.