Abstract: An apparatus include a first circuit and a second circuit. The first circuit may be configured to (i) receive a plurality of sample values from a plurality of images in a video signal and (ii) estimate a plurality of positions of a plurality of maximum values in the images. Each estimation may operate on the sample values in a respective local region oriented parallel to an axis. The second circuit may be configured to track the positions of the maximum values in the images.

Abstract: A method of feature matching is provided. The method includes the steps of (A) determining a set of correspondences between a set of reference feature points for a first image and a set of target feature points for a second image using a processor to compute a descriptor matching function for each pair of reference and target feature points and (B) reducing the set of correspondences using the processor to perform an approximate cross-check to obtain a set of valid correspondences based upon the descriptor matching function computed for each pair of feature points.

Abstract: An apparatus includes an interface and a processor. The interface may be configured to receive an array of scores. The processor may be configured to (i) parse the array of scores into a data flow including one or more operators, (ii) schedule the operators in one or more data paths, (iii) divide the array of scores into blocks of two or more scores by processing the array of scores using the one or more data paths, (iv) compute per-block information using the one or more data paths, and (v) compute local maxima position information for the array of scores by performing block based non-maximum suppression based on the per-block information using the one or more data paths. The data paths are generally implemented with a plurality of hardware circuits.

Abstract: A method of object or feature detection. The method includes the steps of (A) receiving an array of scores and (B) applying a block based non-maximum suppression technique to the array of scores.

Abstract: A method of feature matching is provided. The method includes the steps of (A) determining a set of correspondences between a set of reference feature points for a first image and a set of target feature points for a second image and (B) reducing the set of correspondences while the set of correspondences is being determined using an approximate cross-check to obtain a set of valid correspondences.

Abstract: An apparatus include a processor and a coprocessor. The processor may be configured to track a plurality of positions of a plurality of maximum values in a plurality of images in a video signal. The coprocessor may have a circuit configured to (i) receive a plurality of sample values from the images and (ii) estimate the positions of the maximum values in the images. Each estimation generally includes a parabolic estimation operating on the sample values in a respective local region oriented parallel to an axis. The circuit may be implemented solely in hardware.

Abstract: Embodiments are directed towards enabling digital cameras to digitally process a captured a Low Dynamic Range image sequence at a real time video rate, and to convert the image sequence into an High Dynamic Range (HDR) image sequence using a pipelined architecture. Two or more image frames are captured using different exposure settings and then combined to form a single HDR output frame in a video sequence. The pipelined architecture operate on adjacent image frames by performing an image alignment, an image mixing, and a tone mapping on the adjacent image frames to generate the HDR image sequence.

Abstract: A digital camera captures a sequence of frames such that captured frames of the sequence alternate between sets of frames, in which each frame in the set has a different exposure setting. Each set of frames includes a nominal exposure frame. For each set of frames of the sequence that is captured after the reference set of frames has been captured, a determination is made as to whether or not the captured set of frames should be saved, based, at least in part, on overlap. For each of the saved sets of frames, the frames in the set are aligned with each other, and then image mixing of the frames in the set of frames is performed to generate a high dynamic range image. A panoramic, high dynamic range image is generated from each of the high dynamic range images.

Abstract: A system, method, and computer program product are provided for automatically progressively determining focus depth estimates for an imaging device from defocused images. After a depth-from-defocus (DFD) system generates sometimes-noisy estimates for focus depth and optionally a confidence level that the focus depth estimate is correct, embodiments of the present invention process a sequence of such input DFD measures to iteratively decrease the likelihood of focus depth ambiguity and to increase an overall focus depth estimate confidence level. Automatic focus systems for imaging devices may use the outputs of the embodiments to operate more quickly and accurately, either directly or in combination with other focus depth estimation methods, such as calculated sharpness measures. A depth map of a 3D scene may be estimated for creating a pair of images based on a single image.

Abstract: Embodiments are directed towards enabling digital cameras to digitally process a captured a Low Dynamic Range image sequence at a real time video rate, and to convert the image sequence into an High Dynamic Range (HDR) image sequence using a pipelined architecture. Two or more image frames are captured using different exposure settings and then combined to form a single HDR output frame in a video sequence. The pipelined architecture operate on adjacent image frames by performing an image alignment, an image mixing, and a tone mapping on the adjacent image frames to generate the HDR image sequence.

Abstract: Techniques for creating a High Dynamic Range (HDR) image within a consumer grade digital camera from a series of images of a scene captured at different exposure levels, and displaying the HDR image on the camera's built-in display are provided. The approach employs mixing images of the series to incorporate both scene shadow and highlight details, and the removing of “ghost” image artifacts appearing in the mixed HDR image resulting from movement in the scene over the time the series images are captured. The low computational resource utilization of the image mixing and ghost removal processing operations, along with the ability to commence image mixing and ghost removal prior to the acquisition of all series images, can significantly reduce the time required to generate and display a tone mapped HDR image.

Abstract: A device and methods are provided for calculating depth estimation for a digital imaging device are disclosed and claimed. In one embodiment, a method includes detecting a first image associated with a first focus parameter, detecting a second image associated with a second focus parameter, calculating a statistical representation of a region of interest in the first and second images, and determining a ratio for the region of interest based on the statistical representation. The method may further include determining one or more focus characteristics using a memory table based on the determined ratio for the region of interest, and calculating a focus depth for capture of image data based on the determined one or more focus characteristics associated with the memory table.

Abstract: Techniques for creating a High Dynamic Range (HDR) image within a consumer grade digital camera from a series of images of a scene captured at different exposure levels, and displaying the HDR image on the camera's built-in display are provided. The approach employs mixing images of the series to incorporate both scene shadow and highlight details, and the removing of “ghost” image artifacts appearing in the mixed HDR image resulting from movement in the scene over the time the series images are captured. The low computational resource utilization of the image mixing and ghost removal processing operations, along with the ability to commence image mixing and ghost removal prior to the acquisition of all series images, can significantly reduce the time required to generate and display a tone mapped HDR image.

Abstract: A device and methods are provided for calculating depth estimation for a digital imaging device are disclosed and claimed. In one embodiment, a method includes detecting a first image associated with a first focus parameter, detecting a second image associated with a second focus parameter, calculating a statistical representation of a region of interest in the first and second images, and determining a ratio for the region of interest based on the statistical representation. The method may further include determining one or more focus characteristics using a memory table based on the determined ratio for the region of interest, and calculating a focus depth for capture of image data based on the determined one or more focus characteristics associated with the memory table.