Abstract: A method of calculating warp results for at least one out of driver assistance and autonomous driving, the method may include executing, for each target pixel out of a group of target pixels, a warp calculation process that includes: (a) Receiving, by a first group of processing units of an array of processing units, a first weight and a second weight associated with the target pixel. (b) Receiving, by a second group of processing units of the array, values of neighboring source pixels associated with the target pixel (c) Calculating, by the second group, a warp result based on in response to values of the neighboring source pixels and the pair of weights (d) And providing the warp result to a memory module.

Abstract: An image processing system transforms content images into the style of another reference style image. For example, the system applies a noise mask to generate noisy versions of the content images. The system then recomposes a content image in the style of a reference image by applying computer models to the noisy version of the content image, which reduces artifacts in the stylized image compared to that of a stylized image generated by applying the computer models to the original content image. When the content images are part of a video sequence, the image processing system may adjust the noise mask applied in a subsequent frame such that it tracks the movement of the client device from the current frame to the subsequent frame. This allows the system to reduce artifacts while stylizing the frames of the video in a consistent manner.

Abstract: Various embodiments include automatically selecting and modifying objects within an image that are similar to an object previously selected by a user. A user first selects an object in a displayed image. Object feature descriptors are generated describing a shape formed by edges of the object, and image feature descriptors are generated describing shapes formed by edges automatically detected in the image. The object feature descriptors are compared with the image feature descriptors to automatically identify other objects in the image having edges similar to the selected object. The pixels of the user selected object and the automatically identified objects are modified according to a user specified function.

Abstract: A computer implemented method of matching a medical images of an anatomical structure of a patient's body with an atlas-based representation of the anatomical structure is described. The method includes acquiring patient image data; determining, based on the patient image data, patient substructure data; acquiring general substructure data; determining, for each of the patient substructures and based on the patient substructure data and the general substructure data, substructure matching data; determining, based on the general substructure data and the substructure matching data, anatomical structure atlas data; determining, based on the patient image data and the anatomical structure atlas data, matching transformation data describing an atlas-patient matching transformation between the medical image representation of the anatomical structure and the atlas representation of the anatomical structure.

Abstract: A method for obtaining structural information from a digital image by an electronic device is described. The method includes obtaining a digital image. The method also includes determining a gradient vector for each pixel in a region of interest of the digital image. The method further includes transforming each pixel in the region of interest in accordance with a transform. Transforming each pixel includes determining, for each pixel, a first set of pixels. The first set of pixels includes any pixel along a line that is collinear with or perpendicular to the gradient vector and passes through a pixel location. Transforming each pixel includes incrementing with signed integer values, for each pixel, a first set of values in a transform space corresponding to any of the first set of pixels that are in a first direction of the line.

Abstract: Disclosed are an apparatus of controlling movement of a mobile robot mounted with a wide angle camera and a method thereof. An apparatus of recognizing a position of a mobile robot includes two wide angle cameras which obtain one pair of stereo images on a region of interest including a vertical direction and a horizontal direction in accordance with movement of a mobile robot; an inertial measurement unit (IMU) which obtains inertial information of a mobile robot; a position recognizing unit which predicts a movement point using one between first odometry information calculated based on at least one pair of stereo images and second odometry information calculated based on the inertial information and estimates a current position using the predicted movement point and a previously stored key frame, by a position recognizing unit; and a movement control unit which controls movement of the mobile robot based on the estimated position.

Abstract: Disclosed are an apparatus and a method of updating a key frame of a mobile robot. An apparatus for updating a key frame of a mobile robot includes a key frame initializing unit which initializes seeds which constitute a key frame in a first position of the mobile robot and a key frame updating unit which projects seeds in the initialized key frame onto a first image photographed in the first position to obtain a coordinate according to each of the seeds and projects the seeds with the coordinates onto a second image photographed in a second position in accordance with movement of a mobile robot to update the seeds of the key frame as a projected result.

Abstract: A method, apparatus, and system provide the ability to detect an object framework in an image. A frame (of an image) is obtained. The image is pre-processed to smooth the image. Edges in the image are detected and an edge map is generated. Straight lines are detected from the detected edges in the edge map. One or more quadrangles are assembled from the detected straight lines. The quadrangles are sorted. One of the one or more quadrangles are selected based on the sorting. A selected quadrangle is returned to the user.

Abstract: Image data may be downloaded or otherwise obtained. An application executing on the computing device (or at least in communication with the computing device) can analyze the image data to recognize objects represented in the image data as well as determine locations or regions of the image that include the representations. Candidate regions of interest (e.g., bounding boxes) that include at least one detected object can be generated. A single region—a representative region—can be determined from the candidate regions based on user and/or application-defined criterion. The criteria may help ensure that the representative region includes statistical properties that at least satisfy threshold property levels, such as being a consistent estimator of the candidate regions. Notions of “average” or “median” regions can be applied to generate the representative region.

Abstract: A client device accesses a video input stream from an intermediate device for display. The client device analyzes the video input stream to determine that the video input stream matches a template indicating a portion of the video input stream that is created by the intermediate device. Based on the video input stream matching the template, a video output stream generated by the client device is modified to include the portion of the video input stream generated by the intermediate device. For example, commercials transmitted from a national content provider to a smart TV via a set-top box may be replaced with targeted commercials. During the replacement, informational messages or menus generated by the set-top box may be detected and the replacement video altered by the smart TV to include the messages or menus generated by the set-top box.

Abstract: A system for automated mosaic-based vector editing comprising a mosaic imaging server that assembles image tiles to form larger image mosaics while correcting the image tiles for tonality and other visual characteristics, a vector analysis server that analyzes vector information, a routing calculation server that calculates routes from the vector information, and a rendering engine that produces visualizations from the routing information, and a method for image mosaic creation and correction.

Abstract: An apparatus for generating data includes a display unit that displays an area object the contour of which is extracted from an image to be processed by an image processing application, an operating unit that receives selection conditions for selecting an area object that is intended by a user out of the area objects displayed by the display unit, and a contour extracting unit that extracts a contour of an area object selected based on the selection conditions received by the operating unit. When the contour extracting unit extracts a contour of a selected area object, the display unit displays the selected area object and an unselected area object in a distinguishable manner.

Abstract: Systems and methods in accordance with embodiments of this invention perform depth regularization and semiautomatic interactive matting using images. In an embodiment of the invention, the image processing pipeline application directs a processor to receive (i) an image (ii) an initial depth map corresponding to the depths of pixels within the image, regularize the initial depth map into a dense depth map using depth values of known pixels to compute depth values of unknown pixels, determine an object of interest to be extracted from the image, generate an initial trimap using the dense depth map and the object of interest to be extracted from the image, and apply color image matting to unknown regions of the initial trimap to generate a matte for image matting.

Abstract: A media stream cue point creator receives a media stream comprising at least one of an audio portion or a video portion, wherein the media stream lacks at least one indicator of a content segment within the media stream. The media stream cue point creator identifies a first segment of the plurality of segments of the media stream, wherein the segment corresponds to a segment in a segment reference data store, and creates a cue point associated with the first segment, wherein the cue point identifies at least one of a beginning or an end of the first content segment in the media stream.

Abstract: The present disclosure is directed toward systems and methods for determining the optimal placement, color, and size of an overlay in a digital design. For example, in response to determining that a change to an underlying image of a digital design has caused a loss of readability and/or aesthetic value in the digital design due to the placement of the overlay over the now changed underlying image, one or more embodiments described herein utilize a scoring system to identify optimal placement, color, and size for the overlay in relation to the underlying image in the digital design.

Abstract: Example embodiments include a method that reduces consumption of computer resources in a computer system to reconstruct a shape of a multi-object image using finite terms. The method includes computing an initial function by performing V-system of degree 0 and functions of curves by performing hierarchical V-system. Norms of the functions of curves are compared with a predetermined threshold. A reconstruction function of the shape of the multi-object image is generated by summing the initial function and the functions of curves.

Abstract: A method for processing data includes receiving a depth map of a scene containing at least a part of a body of a humanoid form. The depth map includes a matrix of pixels having respective pixel depth values. A digital processor extracts from the depth map a curvature map of the scene. The curvature map includes respective curvature values and curvature orientations of at least some of the pixels in the matrix. The depth map is segmented using the curvature values and curvature orientations in the curvature map so as to extract three-dimensional (3D) coordinates of one or more limbs of the humanoid form.

Abstract: An apparatus and a method for searching for an image are provided. The apparatus includes an image receiver configured to receive an image to be searched for; an image processor configured to detect an edge of the received image and to filter pixels included on the edge of the received image based on parameters related to gradients of the edge of the received image; and an image search unit configured to search for one or more images related to the image to be searched for based on the filtered pixels included on the edge of the received image.

Abstract: A three-dimensional object printer generates image data of an object being formed in the printer with a plurality of light sources and a plurality of optical sensor arrays. A controller receives the image data and identifies measurements of the object and of the features of the object. The controller compares the measurements to expected measurements and adds material or removes material from the object in response to the identified measurements being outside a predetermined range about the expected measurements.

Abstract: According to examples, inventory, growth, and risk prediction using image processing may include receiving a plurality of images captured by a vehicle during movement of the vehicle along a vehicle path. The images may include a plurality of objects. The images may be pre-processed for feature extraction. A plurality of features of the objects may be extracted from the pre-processed images by using a combination of computer vision techniques. A parameter related to the objects may be determined from the extracted features. A spatial density model may be generated, based on the determined parameter and the extracted features, to provide a visual indication of density of distribution of the objects related to a portion of the images, and/or to provide an alert corresponding to the objects related to the portion of the images.

Abstract: A three-dimensional object printer generates image data of an object being formed in the printer with an optical sensor array and identifies the color of an upper surface of the object. The controller compares the identified color to a predetermined range about an expected color for the upper surface and operates ejectors to eject material of a color different than the identified color in response to the identified color being outside of the predetermined range.

Abstract: Systems and methods identify consumer products in images. Known consumer products are captured as grayscale or color images. They are converted to binary at varying thresholds. Connected components in the binary images identify image features according to pixels of a predetermined size, shape, solidity, aspect ratio, and the like. The image features are stored and searched for amongst image features similarly extracted from unknown images of consumer products. Identifying correspondence between the features of the images lends itself to identifying or not known consumer products.

Abstract: Embodiments of the present invention provide a method, system and computer program product for computer assisted pattern drafting in garment development. In an embodiment of the invention, a pattern making method includes initially acquiring a multiplicity of different two-dimensional image slices of a human form. Thereafter, a panel of a portion of a pattern of a garment is selected for processing in a data processing system and a metric computational rule for the selected panel is mapped to one of the two-dimensional image slices. A measurement of the one of the two-dimensional image slices is then acquired and the mapped metric computational rule is applied using the acquired measurement to produce a measurement for the selected panel.

Abstract: To specify a contour to be detected even when there are a plurality of candidates of the contour on the periphery of a photographing target, an image processing apparatus comprises: a determining unit which detects a plurality of candidate points being the candidates of the contour of a subject based on distance image information of the subject in an image, and determines an inspection-target area in the image based on the detected candidate points; and a specifying unit which detects line segments existing in the inspection-target area determined by the determining unit, based on luminance information of the inspection-target area, and specifies the line segment being the contour of the subject based on the candidate point from the detected line segments.

Abstract: Method for generating piecewise-affine multivariate functions, wherein the online computation of the search tree is performed in order to locate the input value in the polytopes of the partition, and the subsequent generation of the corresponding affine function. It also proposes a configurable and programmable device for generating piecewise-affine multivariate functions composed of an architecture with four functional blocks namely: a control unit block (1), a tree memory block, a parameter memory block and an arithmetic unit block; and it has at least three operating modes which can be selected using different values of a bus (config): writing of the tree memory, writing of the parameter memory and evaluating the affine function. It may include a fourth operating mode, which is the test mode.

Abstract: A method, a system, and a non-transitory computer readable medium for recognizing an object. The method includes emitting an array of infrared rays from an infrared emitter towards a projection region, the projection region including a first object; generating a reference infrared image by recording an intensity of ray reflection from the projection region without the first object; generating a target infrared image by recording the intensity of ray reflection from the projection region with the first object; comparing the target infrared image to the reference infrared image to generate a predetermined intensity threshold; and extracting the first object from the target infrared image, if the intensity of ray reflection of the target infrared image of the first object exceeds the predetermined intensity threshold.

Abstract: Object recognition by point-of-sale camera systems is aided by first removing perspective distortion. Yet pose of the object—relative to the system—depends on actions of the operator, and is usually unknown. Multiple trial counter-distortions to remove perspective distortion can be attempted, but the number of such trials is limited by the frame rate of the camera system—which limits the available processing interval. One embodiment of the present technology examines historical image data to determine counter-distortions that statistically yield best object recognition results. Similarly, the system can analyze historical data to learn what sub-parts of captured imagery most likely enable object recognition. A set-cover strategy is desirably used. In some arrangements, the system identifies different counter-distortions, and image sub-parts, that work best with different clerk- and customer-operators of the system, and processes captured imagery accordingly.

Abstract: Biometric data is collected to obtain more detailed, connected, and reliable feedback data from users of an interactive software system that has a more empirical and objective basis. The biometric data is then used to create emotional pattern predictive model data representing emotional pattern predictive models associated with users of the interactive software system. The individual emotional pattern predictive models associated with multiple users of the interactive software system are then analyzed and processed to generate emotional pattern profile data for categories of users. These biometric data based predictive models are then used for targeted product diagnosis, targeted interventions, targeted marketing/upsell attempts, and grouping and analysis of feedback and user categories and feedback sources.

Abstract: Methods, apparatus, and computer readable media that are related to 3D object detection and pose determination and that may optionally increase the robustness and/or efficiency of the 3D object recognition and pose determination. Some implementations are generally directed to techniques for generating an object model of an object based on model point cloud data of the object. Some implementations of the present disclosure are additionally and/or alternatively directed to techniques for application of acquired 3D scene point cloud data to a stored object model of an object to detect the object and/or determine the pose of the object.

Abstract: An image quality enhancing apparatus which make a learning-type image quality enhancing method utilizing a sparse expression practical are provided. The apparatus calculates, from the feature quantity of an image, coefficients of low-image-quality base vectors expressing a feature quantity with a linear sum and generates the image with the image quality enhanced by calculating a linear sum of high-image-quality base vectors using the calculated coefficient. When calculating the coefficient, the number of base vectors with non-zero coefficients is determined, the determined number of base vectors is selected, and a solution of a coefficient matrix is calculated by assuming the coefficients of the base vectors other than the selected base vectors are zero. The amount of processes necessary for obtaining a sparse solution of a coefficient matrix can be reduced by adjusting the number of base vectors with non-zero coefficients, and a practical image quality enhancing apparatus can be realized.

Abstract: In one example, a video coding device is configured to intra-predict a block of video data, using values of pixels along a primary boundary of the block, to form a predicted block, determine whether to filter the predicted block using data of a secondary boundary of the block, and filter the predicted block using data of the secondary boundary in response to determining to filter the predicted block. The video coding device may determine whether to filter the predicted block based on a comparison of a Laplacian value or a gradient difference value to a threshold. The determination of whether to filter the predicted block may be based at least in part on a boundary relationship, e.g., the relationship of one boundary to another, or of a boundary to pixel values of the predicted block.

Abstract: Disclosed herein is a method that comprises obtaining an image of a network section through which flow occurs; where the flow is selected from a group consisting of fluid, electrons, protons, neutrons and holes; subjecting the image to a low pass filter to increase contrast in portions of the network sections; computing a local mean of visible light intensity at each pixel that is present in the image; calculating a visible light intensity difference between each pixel and the local mean of visible light intensity and producing a differentiated image using this calculation; creating a base image of the differentiated image; where the base image comprises a hand segmented gold standard dataset; removing objects below a minimum threshold size from the base image; and retaining the remaining objects if they approximate the line or spine.

Abstract: An image processing apparatus includes: a splitting unit that splits each of two images into a plurality of regions; an extracting unit that extracts a first value indicating the highest similarity in an array, in the array values indicating similarity between corresponding split images between the two images are arranged, and that extracts a second value indicating highest similarity after excluding similarity in an area including a position of the first value from targets; and a controlling unit that controls to perform position alignment of the two images by excluding a value, of the values indicating the similarity of each of the split images, indicating similarity, a difference between the first value and the second value is less than or equal to a predetermined threshold in the similarity.

Abstract: An image quality enhancing apparatus, an image display apparatus, an image quality enhancing method, and a computer readable storage medium which make a learning-type image quality enhancing method utilizing a sparse expression practical are provided. The image quality enhancing apparatus calculates, from the feature quantity of an image, coefficients of low-image-quality base vectors expressing a feature quantity with a linear sum and generates the image with the enhanced image quality by calculating a linear sum of high-image-quality base vectors using the calculated coefficient. When calculating the coefficient, T base vectors highly influential on the feature quantity are selected from among a plurality of base vectors and an analytic solution making L2 norm of a coefficient matrix ? as small as possible is calculated. A sparse solution of the coefficients can be obtained without using the iteration method and a practical image quality enhancing apparatus can be realized.

Abstract: An apparatus for detecting a feature in an image includes an image input section for receiving at least part of the image in the form of image data having a plurality of pixels, the plurality of pixels comprising a plurality of non-border pixels, a feature detection module adapted to attribute a feature probability value to each of the pixels of the image data, and an extremum determination module for determining at least one local extremum among the feature probability values, wherein the extremum determination module is adapted to output, for each of the plurality of pixels, a final indication if the feature probability value of the pixel in question is a local extremum.

Abstract: Smoothing images using machine learning is described. In one or more embodiments, a machine learning system is trained using multiple training items. Each training item includes a boundary shape representation and a positional indicator. To generate the training item, a smooth image is downscaled to produce a corresponding blocky image that includes multiple blocks. For a given block, the boundary shape representation encodes a blocky boundary in a neighborhood around the given block. The positional indicator reflects a distance between the given block and a smooth boundary of the smooth image. In one or more embodiments to smooth a blocky image, a boundary shape representation around a selected block is determined. The representation is encoded as a feature vector and applied to the machine learning system to obtain a positional indicator. The positional indicator is used to compute a location of a smooth boundary of a smooth image.

Abstract: Disclosed are systems, methods and computer program products for using prior frame data for OCR processing of frames in video sources to detect natural language text therein. An example includes receiving a frame from a video source and retrieving prior frame data associated with the video source. The OCR-processing includes using prior frame data to detect blobs similar to blobs described in the prior frame data; using detected similar blobs to detect in the frame character candidates similar to character candidates described in the prior frame data; using detected similar character candidates to detect in the frame text candidates similar to text candidates described in the prior frame data; and using detected similar text candidates to detect in the frame text strings similar to text strings described in the prior frame data.

Abstract: A mechanism is described for facilitating code filters for coded light depth acquisition in depth images at computing devices according to one embodiment. A method of embodiments, as described herein, includes detecting a code image of an object comprising pixels of code values and pixels of metadata values including confidence and code transition locations, and computing a vertical filter to be applied to the code image to smooth out the code transitions along vertical directions. The method further include computing a horizontal filter to be applied to the code image to smooth out the code transitions along horizontal directions, and computing a consistency filter to be applied to the code image to increase an accuracy of the code values and mark inconsistent pixels as invalid.

Abstract: An image process to be performed on an edge of a character or a line is not performed on pixels included in a mosaic image.

Abstract: Systems and methods are provided for selecting feature points within an image. A plurality of candidate feature points are identified in the image. A plurality of feature points are selected for each of the plurality of candidate feature points, a plurality of sets of representative pixels. For each set of representative pixels, a representative value is determined as one of a maximum chromaticity value and a minimum chromaticity value from the set of representative pixels. A score is determined for each candidate feature point from the representative values for the plurality of sets of representative pixels associated with the candidate feature point. The feature points are selected according to the determined scores for the plurality of candidate feature points.

Abstract: A method of increasing resolution of an image includes generating vector contours associated with a first image and scaling the vector contours to a second resolution. The first image has a first resolution, and the second resolution is greater than the first resolution. The vector contours are rendered to generate a guiding image at the second resolution, and a second image is generated from the first image based on the guiding image, by using joint upsampling. The second image is generated at the second resolution. The vector contours can be generated by bitmap tracing binary images at different quantization levels. An apparatus and computer readable device implementing the method of increasing the resolution of an image are also provided.

Abstract: A method for training a neural network to perform assessments of image quality is provided. The method includes: inputting into the neural network at least one set of images, each set including an image and at least one degraded version of the image; performing comparative ranking of each image in the at least one set of images; and training the neural network with the ranking information. A neural network and image signal processing tuning system are disclosed.

Abstract: A system and method for providing a video merged from two independent video sources to a display is disclosed. The system and method includes receiving an enhanced vision video from an enhanced vision system, receiving a synthetic vision video from a synthetic vision system and selecting an enhanced frame in the enhanced vision video. The system and method also includes selecting a synthetic frame from the synthetic vision video corresponding to the selected enhanced frame, analyzing the enhanced frame to detect objects according to a first algorithm, analyzing the synthetic frame to detect default frame segments, merging the enhanced frame and the synthetic frame to provide a merged frame that includes detected objects and detected default frame segments and displaying the merged frame on a display.

Abstract: Interactive mesh deformation for in-plane 3D segmentation/delineation for radiation therapy planning done on a slice by slice basis of a region/a volume of interest (VOI, ROI). Segmentation starts by some automatic 3D algorithm approximating the organ surface roughly by some triangular surface mesh which mesh is afterwards manually refined by the user who deforms it to bring it closer to the region of interest. The deformation is an invertible, i.e. one-to-one, mapping avoiding self-intersections of the deformed mesh thereby preserving the topology of the anatomy. The deformation mapping involves a Gaussian function (Gaussian deformation kernel) restricting the deformation to a local region. The user picks with the pointer a start point on a selected image slice through the volume and moves it to some end point. The distance the mesh vertices move decreases exponentially with the distance to the start point.

Abstract: The present invention generally relates to automatic detection of video artifacts. The present invention relates to automatically detect out the images with visible artifacts due to STB decoding error based on a generated artificial edge map. In particular, the application teaches a method to detect out the images with the visible artifacts and how to identify artificial edges from texture (natural) edges. The present system identifies that artificial edges are most significant in local area, while texture edges are often together with some other texture edges.

Abstract: A people counting device includes an edge extracting unit configured to extract an edge from a planar image of a target area, and a circle candidate detecting unit configured to detect a circle candidate included in the planar image based on the edge extracted by the edge extracting unit. The people counting device further includes a person determining unit configured to calculate a brightness gradient for each edge pixel constituting an edge of each circle candidate detected by the circle candidate detecting unit and determine that a circle candidate whose uniformity of brightness gradients for the edge pixels of the circle candidate is higher than a reference is a person's head portion, and a people counting unit configured to count the number of circle candidates determined to be a person's head portion by the person determining unit.

Abstract: An apparatus for warning an obstacle of a vehicle includes an image obtaining device configured to take an image around the vehicle through image sensors. An image segmentation device is configured to segment a current reference image obtained in blocks of an object. A motion estimator is configured to estimate two dimensional motion information of the object. A variation estimator is configured to estimate distance information between the object and the vehicle. A relative motion estimator is configured to estimate three dimensional relative motion information of the object by combining the two dimensional motion information and the distance information. A collision time estimator is configured to estimate a collision time between the object and the vehicle by using the three dimensional relative motion information. An image processor is configured to adjust a brightness of a corresponding segmented block. A display is configured to display the image.

Abstract: A method and system displaying and managing images of consumer products with cloud computing. A layout for plural selected consumer products is selected. An N-layer digital image of a shelf layout on which consumer products are displayed is created and stored in one or more cloud storage objects. The created N-layer digital image includes an M-layer hierarchy of vector images and/or visual overlays stored in one or more cloud storage objects in progressive resolution format and allows progressive resolution display without loss of image quality on the selected plural consumer products that appear in the N-layer digital image. The created N-layer digital image is displayed via a cloud communications network. The created image provides a virtual shopping experience that emulates a shopping experience in an actual retail store.

Abstract: Systems, methods performed by data processing apparatus and computer storage media encoded with computer programs for receiving content items, each of which is to be displayed upon request as a component of a page bearing other content, manipulating a visual appearance of at least one of the content items such that the content item is more likely to appear visually merged with other content when displayed as a component of a page bearing other content, and storing the manipulated at least one content item for subsequent display as a component of a page bearing other content.

Abstract: An image processing device includes an edge direction determination unit, a filter coefficient calculation unit, and a filter processing unit. The edge direction determination unit determines a first edge direction of an edge including a first pixel of input image data, and calculates a first reliability value of the determined edge direction corresponding to the first pixel. The filter coefficient calculation unit calculates a first filter coefficient corresponding to the first pixel, a second filter coefficient corresponding to a second pixel, and a third filter coefficient corresponding to a third pixel at least based on the first reliability value of the first edge direction. The filter processing unit performs filter processing on the input image data on the basis of the calculated first through third filter coefficients, and outputs output image data.