Abstract:
A method performed by an electronic device is described. The method includes obtaining a motion vector map based on at least two images. The motion vector map has fewer motion vectors than a number of pixels in each of the at least two images. The method also includes obtaining a feature point from one of the at least two images. The method further includes performing a matching operation between a template associated with the feature point and at least one search space based on the motion vector map. The method additionally includes determining a motion vector corresponding to the feature point based on the matching operation.
Abstract:
A method performed by an electronic device is described. The method includes obtaining a motion vector map based on at least two images. The motion vector map has fewer motion vectors than a number of pixels in each of the at least two images. The method also includes obtaining a feature point from one of the at least two images. The method further includes performing a matching operation between a template associated with the feature point and at least one search space based on the motion vector map. The method additionally includes determining a motion vector corresponding to the feature point based on the matching operation.
Abstract:
Method and apparatus for reducing random noise in digital video streams are described. In one innovative aspect, a device for reducing noise of a video stream is provided. The device includes a ringing noise detector configured to identify ringing noise in an image included in the video stream. The device further includes a block detector configured to identify a block pattern in the image included in the video stream, the block detector configured to identify block patterns of a predetermined size and block patterns of an arbitrary size. The device also includes a noise reducer configured to filter the image based on the identified ringing noise and the block pattern.
Abstract:
A method for determining a histogram is described. The method includes storing a plurality of histograms in a memory bank, each histogram corresponding to a group of pixels in a region of interest of an image. The method also includes initiating transfer of one or more histograms between the memory bank and a local memory. The method further includes finding, for an incoming pixel, weights of each bin for the one or more histograms stored in the local memory. The method additionally includes adding the weights to the one or more histograms stored in the local memory. The method also includes transferring one or more updated histograms from the local memory to the memory bank. The method further includes replacing a corresponding one or more histograms in the memory bank with the one or more updated histograms.
Abstract:
Method and apparatus for reducing random noise in digital video streams are described. In one innovative aspect, the device includes a noise estimator. The device also includes a motion detector configured to determine a motion value indicative of motion between two frames of the video stream, the motion value based at least in part on the noise value. The device further includes a spatial noise reducer configured to filter the image data based at least in part on a blending factor and the noise value. The device also includes a temporal noise reducer configured to filter the video data based on the motion value and the noise value. The device also includes a blender configured to blend the spatial and temporal filtered values to provide a weighted composite filtered output image.
Abstract:
Method and apparatus for reducing random noise in digital video streams are described. In one innovative aspect, the device includes a noise estimator. The device also includes a motion detector configured to determine a motion value indicative of motion between two frames of the video stream, the motion value based at least in part on the noise value. The device further includes a spatial noise reducer configured to filter the image data based at least in part on a blending factor and the noise value. The device also includes a temporal noise reducer configured to filter the video data based on the motion value and the noise value. The device also includes a blender configured to blend the spatial and temporal filtered values to provide a weighted composite filtered output image.
Abstract:
A classifier for detecting objects in images can be configured to receive features of an image from a feature extractor. The classifier can determine a feature window based on the received features, and allows access by each decision tree of the classifier to only a predetermined area of the feature window. Each decision tree of the classifier can compare a corresponding predetermined area of the feature window with one or more thresholds. The classifier can determine an object in the image based on the comparisons. In some examples, the classifier can determine objects in a feature window based on received features, where the received features are based on color information for an image.
Abstract:
Systems and methods for improving the contrast of image frames are disclosed. In one embodiment, a system for improving the contrast of image frames includes a control module configured to create an intensity histogram for an image frame, define a set of markers on an intensity range of the histogram, assign a blend factor to each marker, calculate a blend factor for each original pixel of the image, obtain a first equalized pixel output value, calculate a final equalized pixel output value using the blend factor, the first equalized pixel output value, and an original pixel value, and output new pixel values that constitute the output image.