Abstract: An image processing system comprises an image processor having image processing circuitry and an associated memory. The image processor is configured to identify a region of interest in an amplitude image, to detect one or more relatively low gradient regions in the region of interest, to reconstruct depth information for said one or more relatively low gradient regions, to extend the reconstructed depth information beyond said one or more relatively low gradient regions to additional pixels of the region of interest, and to generate a depth image utilizing at least portions of the reconstructed depth information and the extended reconstructed depth information. The image processor in some embodiments is adapted for coupling to an active lighting image sensor, such as an infrared sensor that does not provide depth information corresponding to the amplitude image, or an SL or ToF sensor that provides depth information corresponding to the amplitude image.

Abstract: In one embodiment, an image processor is configured to obtain a plurality of phase images for each of first and second depth frames. For each of a plurality of pixels of a given one of the phase images of the first depth frame, the image processor determines an amount of movement of a point of an imaged scene between the pixel of the given phase image and a pixel of a corresponding phase image of the second depth frame, and adjusts pixel values of respective other phase images of the first depth frame based on the determined amount of movement. A motion compensated first depth image is generated utilizing the given phase image and the adjusted other phase images of the first depth frame. Movement of a point of the imaged scene is determined, for example, between pixels of respective n-th phase images of the first and second depth frames.

Abstract: An image processing system comprises an image processor configured to identify edges in an image, to apply a first type of filtering operation to portions of the image associated with the edges, and to apply a second type of filtering operation to one or more other portions of the image. By way of example only, in a given embodiment a clustering operation is applied to the image to identify a plurality of clusters, a first set of edges comprising edges of the clusters is identified, an edge detection operation is applied to the image to identify a second set of edges, a third set of edges is identified based on the first and second sets of edges, and the first type of filtering operation is applied to portions of the image associated with one or more edges of the third set of edges.

Abstract: An image processing system comprises an image processor configured to perform an edge detection operation on a first image to obtain a second image, to identify particular edges of the second image that exhibit at least a specified reliability, and to generate a third image comprising the particular edges and excluding other edges of the second image. By way of example only, in a given embodiment the first image may comprise a depth image generated by a depth imager, the second image may comprise an edge image generated by applying the edge detection operation to the depth image, and the third image may comprise a modified edge image having only the particular edges that exhibit at least the specified reliability.

Abstract: An image processing system comprises an image processor configured to perform first and second edge detection operations on respective first and second images to obtain respective first and second edge images, to apply a joint edge weighting operation using edges from the first and second edge images, to generate an edge mask based on results of the edge weighting operation, to utilize the edge mask to obtain a third edge image, and to generate a third image based on the third edge image. By way of example only, in a given embodiment the first image may comprise a first depth image generated by a depth imager, the second image may comprise a two-dimensional image of substantially the same scene as the first image, and the third image may comprise an enhanced depth image having enhanced edge quality relative to the first depth image.

Abstract: An image processing system comprises an image processor configured to identify edges in an image, to apply a first type of filtering operation to portions of the image associated with the edges, and to apply a second type of filtering operation to one or more other portions of the image. By way of example only, in a given embodiment a clustering operation is applied to the image to identify a plurality of clusters, a first set of edges comprising edges of the clusters is identified, an edge detection operation is applied to the image to identify a second set of edges, a third set of edges is identified based on the first and second sets of edges, and the first type of filtering operation is applied to portions of the image associated with one or more edges of the third set of edges.

Abstract: A depth imager is configured to generate a first depth image using a first depth imaging technique, and to generate a second depth image using a second depth imaging technique different than the first depth imaging technique. At least portions of the first and second depth images are merged to form a third depth image. The depth imager comprises at least one sensor including a single common sensor at least partially shared by the first and second depth imaging techniques, such that the first and second depth images are both generated at least in part using data acquired from the single common sensor. By way of example, the first depth image may comprise a structured light (SL) depth map generated using an SL depth imaging technique, and the second depth image may comprise a time of flight (ToF) depth map generated using a ToF depth imaging technique.

Abstract: An image processing system comprises an image processor configured to perform an edge detection operation on a first image to obtain a second image, to identify particular edges of the second image that exhibit at least a specified reliability, and to generate a third image comprising the particular edges and excluding other edges of the second image. By way of example only, in a given embodiment the first image may comprise a depth image generated by a depth imager, the second image may comprise an edge image generated by applying the edge detection operation to the depth image, and the third image may comprise a modified edge image having only the particular edges that exhibit at least the specified reliability.

Abstract: An image processing system comprises an image processor configured to perform first and second edge detection operations on respective first and second images to obtain respective first and second edge images, to apply a joint edge weighting operation using edges from the first and second edge images, to generate an edge mask based on results of the edge weighting operation, to utilize the edge mask to obtain a third edge image, and to generate a third image based on the third edge image. By way of example only, in a given embodiment the first image may comprise a first depth image generated by a depth imager, the second image may comprise a two-dimensional image of substantially the same scene as the first image, and the third image may comprise an enhanced depth image having enhanced edge quality relative to the first depth image.

Abstract: An image processing system comprises an image processor having image processing circuitry and an associated memory. The image processor is configured to implement a gesture recognition system comprising a static pose recognition module. The static pose recognition module is configured to identify a hand region of interest in at least one image, to perform a skeletonization operation on the hand region of interest, to determine a main direction of the hand region of interest utilizing a result of the skeletonization operation, to perform a scanning operation on the hand region of interest utilizing the determined main direction to estimate a plurality of hand features that are substantially invariant to hand orientation, and to recognize a static pose of the hand region of interest based on the estimated hand features.

Abstract: An image processing system comprises an image processor configured to establish a main processing thread and a parallel processing thread for respective portions of a multithreaded gesture recognition process. The parallel processing thread is configured to utilize buffer circuitry of the image processor, such as one or more double buffers of the buffer circuitry, so as to permit the parallel processing thread to run asynchronously to the main processing thread. The parallel processing thread implements one of noise estimation, background estimation and static hand pose recognition for the multithreaded gesture recognition process. Additional processing threads may be established to run in parallel with the main processing thread. For example, the image processor may establish a first parallel processing thread implementing the noise estimation, a second parallel processing thread implementing the background estimation, and a third parallel processing thread implementing the static hand pose recognition.

Abstract: An image processing system comprises an image processor having image processing circuitry and an associated memory. The image processor is configured to implement a gesture recognition system comprising a static pose recognition module. The static pose recognition module is configured to identify a region of interest in at least one image, to represent the region of interest as a segmented region of interest comprising a union of segment sets from respective ones of a plurality of lines, to estimate features of the segmented region of interest, and to recognize a static pose of the segmented region of interest based on the estimated features. The lines from which the respective segment sets are taken illustratively comprise respective parallel lines configured as one of horizontal lines, vertical lines and rotated lines. A given one of the segments in one of the sets may be represented by a pair of segment coordinates.

Abstract: An image processing system comprises an image processor implemented using at least one processing device and adapted for coupling to an image source, such as a depth imager. The image processor is configured to compute a convergence matrix and a noise threshold matrix, to estimate background information of an image utilizing the convergence matrix, and to eliminate at least a portion of the background information from the image utilizing the noise threshold matrix. The background estimation and elimination may involve the generation of static and dynamic background masks that include elements indicating which pixels of the image are part of respective static and dynamic background information. The computing, estimating and eliminating operations may be performed over a sequence of depth images, such as frames of a 3D video signal, with the convergence and noise threshold matrices being recomputed for each of at least a subset of the depth images.

Abstract: A method for double precision approximation of a single precision operation is disclosed. The method may include steps (A) to (B). Step (A) may store an input value in a processor. The processor generally implements a plurality of first operations in hardware. Each first operation may receive a first variable as an argument. The first variable may be implemented in a fixed point format at a single precision. The input value may be implemented in the fixed point format at a double precision. Step (B) may generate an output value by emulating a selected one of the first operations using the input value as the argument. The emulation may utilize the selected first operation in hardware. The output value may be implemented in the fixed point format at the double precision. The emulation is generally performed by a plurality of instructions executed by the processor.

Abstract: An image processing system comprises an image processor configured to identify one or more potentially defective pixels associated with at least one depth artifact in a first image, and to apply a super resolution technique utilizing a second image to reconstruct depth information of the one or more potentially defective pixels. Application of the super resolution technique produces a third image having the reconstructed depth information. The first image may comprise a depth image and the third image may comprise a depth image corresponding generally to the first image but with the depth artifact substantially eliminated. An additional super resolution technique may be applied utilizing a fourth image. Application of the additional super resolution technique produces a fifth image having increased spatial resolution relative to the third image.

Abstract: An apparatus generally having a first circuit and a second circuit is disclosed. The first circuit may be configured to generate a first sample by filtering an input vector based on (a) a filter vector and (b) a stochastic vector. Each of a plurality of components in the stochastic vector generally has a respective random value. The first circuit may also be configured to generate a second sample as a difference between a third sample and the first sample. The third sample may be received from a network as an echo. The second circuit may be configured to update a subset of a plurality of taps of the filtering where a corresponding one of the components of the stochastic vector has a first value of the random values.

Abstract: A method for double precision approximation of a single precision operation is disclosed. The method may include steps (A) to (B). Step (A) may store an input value in a processor. The processor generally implements a plurality of first operations in hardware. Each first operation may receive a first variable as an argument. The first variable may be implemented in a fixed point format at a single precision. The input value may be implemented in the fixed point format at a double precision. Step (B) may generate an output value by emulating a selected one of the first operations using the input value as the argument. The emulation may utilize the selected first operation in hardware. The output value may be implemented in the fixed point format at the double precision. The emulation is generally performed by a plurality of instructions executed by the processor.

Abstract: An apparatus generally having a first circuit and a second circuit is disclosed. The first circuit may be configured to generate a first sample by filtering an input vector based on (a) a filter vector and (b) a stochastic vector. Each of a plurality of components in the stochastic vector generally has a respective random value. The first circuit may also be configured to generate a second sample as a difference between a third sample and the first sample. The third sample may be received from a network as an echo. The second circuit may be configured to update a subset of a plurality of taps of the filtering where a corresponding one of the components of the stochastic vector has a first value of the random values.