Abstract: A hybrid computing system configured to estimate a derivative of a parameter-dependent physical quantity that is dependent on a first control parameter ? of a parameterised quantum evolution executed by the quantum computing system. The classical computing system determines, based on an input bounding value and phase-correction value, a subset multiset of shift-values which define an equivalent subset multiset of trial control parameter values and corresponding weighting values and summation factors such that the trial control parameter values obey a targeted probability distribution. The quantum computing system executes the parameterised quantum evolution at the trial control parameter values and measures a parameter-dependent physical quantity for each trial control parameter value.

Abstract: A method for providing alternative object identifiers for objects of an address space of a server within an OPC UA based communication environment, wherein each object of the address space of the server is uniquely identified by a conventional object identifier, wherein at least one additional identifier is defined and is stored in a directory of additional identifiers defined for this address space of the server, and wherein an alternative object identifier also uniquely identifying the object is formed for each object of the address space of the server, whereby the additional identifier is combined with the conventional object identifier of the respective object according to a determined pattern. Another method for validating alternative object identifiers and a method for determining references of object identifiers, as well as a server, a system, and a computer program product designed to carry out at least one of the methods.

Abstract: A method and an apparatus for generating lens-related metadata for a light field imaging device. An image renderer generates a display image from a light field capture using a lens model. A metadata assembler then outputs parameters of the lens model used for generating the display image as lens-related metadata for the light field imaging device.

Abstract: In order to objectively and efficiently measure, visualize and evaluate the quality of images in terms of sharpness, a method for determining a sharpness metric (S) of an image is described. The method includes performing edge detection that results in gradients for the pixels of the image, determining a value representing a contrast metric C of the image, calculating at least three different thresholds (t1,t2,t3) from the image content, and classifying the pixels according to their gradient into at least four groups defined by the thresholds. The sharpness metric (S) is calculated from relationships between the amounts of pixels in the different groups and a multiplicative factor (m) between the at least three thresholds.

Abstract: In order to objectively and efficiently measure, visualize and evaluate the quality of images in terms of sharpness, a method for determining a sharpness metric (S) of an image is described. The method includes performing edge detection that results in gradients for the pixels of the image, determining a value representing a contrast metric C of the image, calculating at least three different thresholds (t1, t2,t3) from the image content, and classifying the pixels according to their gradient into at least four groups defined by the thresholds. The sharpness metric (S) is calculated from relationships between the amounts of pixels in the different groups and a multiplicative factor (m) between the at least three thresholds.

Abstract: Results of automatic detection of dirt or other non-steady defects in a sequence of digitized image frames can be unreliable. Here, a determination of a detection of a defective object to be replaced by a replacement pattern in a frame of a sequence of image frames as a misdetection is presented that comprises determining a value of a first similarity measure between a boundary of the detected defective object and a boundary of the replacement pattern and determining a value of a second similarity measure between the detected defective object and the replacement pattern. The detection of the defective object is determined as a misdetection if at least one of the following holds true: the value of the first similarity measure is outside of a corresponding first similarity acceptance range and the value of the second similarity measure is inside of a corresponding second similarity acceptance range.

Abstract: A method and an apparatus for generating lens-related metadata for a light field imaging device. An image renderer generates a display image from a light field capture using a lens model. A metadata assembler then outputs parameters of the lens model used for generating the display image as lens-related metadata for the light field imaging device.

Abstract: A method and apparatus for deriving a hash value from a single channel image, comprising: size reducing the image into first resized images having different horizontal and vertical size, deriving therefrom horizontal difference images comprising horizontal neighboring pixel differences, size reducing the image into second resized images having different horizontal and vertical size, deriving therefrom vertical difference images comprising vertical neighboring pixel differences, and combining the sign bits of the horizontal neighboring pixel differences and the sign bits of the vertical neighboring pixel differences in a predefined order into bits of the hash value.

Abstract: A method and an apparatus for handling a defect object in an image. A light field information retrieving unit retrieves a light field capture of the image. A view generator generates a center view and two or more side views from the light field capture. A defect determining unit then determines a defect object in the image through a comparison of the center view and the two or more side views.

Abstract: Dirt or other non-steady defects are detected in a frame of a sequence of digitized image frames. No determination of motion vectors for motion compensation is required. Instead, absolute motion values for a plurality of pixels of the frame relative to a preceding frame and to a succeeding frame of the sequence are determined. Based on the assumption that motion is usually smooth in the sequence, temporal coherence violations between the frame and the preceding frame and between the frame and the succeeding frame are detected for the pixels, depending on the absolute motion values. Pixels of the plurality of pixels are determined as defective if corresponding temporal coherence violations are detected between the frame and the preceding frame and the succeeding frame.

Abstract: Results of automatic detection of dirt or other non-steady defects in a sequence of digitized image frames can be unreliable. Here, a determination of a detection of a defective object to be replaced by a replacement pattern in a frame of a sequence of image frames as a misdetection is presented that comprises determining a value of a first similarity measure between a boundary of the detected defective object and a boundary of the replacement pattern and determining a value of a second similarity measure between the detected defective object and the replacement pattern. The detection of the defective object is determined as a misdetection if at least one of the following holds true: the value of the first similarity measure is outside of a corresponding first similarity acceptance range and the value of the second similarity measure is inside of a corresponding second similarity acceptance range.

Abstract: Absolute motion values between two frames of a sequence of successive image frames are estimated based on a determination of a plurality of pyramid levels of Gaussian pyramid representations of the two frames. The Gaussian pyramid representations of the two frames are pyramid level-wise compared to generate arrays of pixel-by-pixel distance measures between corresponding pyramid levels. Arrays of motion values from the distance measures are pyramid level-wise determined, weighted by level values assigned to the corresponding pyramid levels. Then, recursively from top to bottom pyramid levels, weighted motion values of corresponding motion arrays are transferred to the motion array corresponding to a next lower pyramid level if they exceed the corresponding weighted motion values of said next lower pyramid level.

Abstract: A method and an apparatus for automatic restoration of an image or a sequence of images, e.g. motion picture films, are disclosed, which facilitate removal of artifacts within the image or the sequence of images. The restoration is split into a detection process, a quality control process, and a removal process. In the detection process artifacts in the image or the sequence of images are detected and information about the detected artifacts is stored in a metadata database. In the subsequent quality control process the information about the detected artifacts is reviewed by an operator. In the removal process one or more of the detected artifacts are removed from the image or the sequence of images based on the information about the detected artifacts stored in the metadata database.

Abstract: A method and an apparatus for generating metadata for digital content are described, which allow to review the generated metadata already in course of ongoing generation of metadata. The metadata generation is split into a plurality of processing tasks, which are allocated to two or more processing nodes. The metadata generated by the two or more processing nodes is gathered and visualized on an output unit.

Abstract: In accordance with an exemplary embodiment of the present invention, a method for measuring a quality parameter of an optical storage system comprising a non-diffraction-limited optical storage medium and a readout device, the method comprising the process of deriving an impulse response of the optical storage system, and the process of analyzing the impulse response to determine at least one of a width of the impulse response and a skewness of the impulse response as the quality parameter.

Abstract: A method for interactive review of two or more datasets and an apparatus configured to enable interactive review of two or more datasets are described. A first dataset and a second dataset are retrieved via an input. A processor generates representative values from the first dataset for a coarse view of the first dataset and for a fine view of the first dataset. The processor also generates representative values from the second dataset for a coarse view of the second dataset. A user interface generator includes the coarse view of the first dataset, the coarse view of the second dataset, and the fine view of the first dataset in a graphic user interface. Upon reception of a user request via a user input 32 to select the second dataset, the processor generates representative values from the second dataset for a fine view of the second dataset. The user interface generator then replaces the fine view of the first dataset in the graphic user interface with the fine view of the second dataset.

Abstract: A method for interactive review of a dataset and an apparatus configured to enable interactive review of a dataset are described. A user request to review the dataset is received via user input. Responsive to this request, a processor generates representative values from the dataset for a coarse view of the dataset and for a fine view of the dataset. A user interface generator then outputs a graphic user interface displaying the coarse view of the dataset and the fine view of the dataset.

Abstract: The error correction capability of block codes can be doubled if error locations are known. Prior art approaches for error location detection always involve adding dedicated redundant data which then are evaluated to yield error location information. The present invention proposes and describes how error location information in the form of clues is derived from given DC control bits that are anyway present in a data stream.

Abstract: A method and an apparatus for automatic restoration of an image or a sequence of images, e.g. motion picture films, are disclosed, which facilitate removal of artifacts within the image or the sequence of images. The restoration is split into a detection process, a quality control process, and a removal process. In the detection process artifacts in the image or the sequence of images are detected and information about the detected artifacts is stored in a metadata database. In the subsequent quality control process the information about the detected artifacts is reviewed by an operator. In the removal process one or more of the detected artifacts are removed from the image or the sequence of images based on the information about the detected artifacts stored in the metadata database.

Abstract: In accordance with an exemplary embodiment of the present invention, a method for measuring a quality parameter of an optical storage system comprising a non-diffraction-limited optical storage medium and a readout device, the method comprising the process of deriving an impulse response of the optical storage system, and the process of analyzing the impulse response to determine at least one of a width of the impulse response and a skewness of the impulse response as the quality parameter.