Abstract: A method of generating a high dynamic range (HDR) image is provided that includes capturing a long exposure image and a short exposure image of a scene, computing a merging weight for each pixel location of the long exposure image based on a pixel value of the pixel location and a saturation threshold, and computing a pixel value for each pixel location of the HDR image as a weighted sum of corresponding pixel values in the long exposure image and the short exposure image, wherein a weight applied to a pixel value of the pixel location of the short exposure image and a weight applied to a pixel value of the pixel location in the pixel long exposure image are determined based on the merging weight computed for the pixel location and responsive to motion in a scene of the long exposure image and the short exposure image.

Abstract: A method of determining a pose of a camera is described. The method comprises analyzing changes in an image detected by the camera using a plurality of sensors of the camera; determining if a pose of the camera is incorrect; determining which sensors of the plurality of sensors are providing the most reliable image data; and analyzing data from the sensors providing the most reliable image data.

Abstract: A method of generating a high dynamic range (HDR) image is provided that includes capturing a long exposure image and a short exposure image of a scene, computing a merging weight for each pixel location of the long exposure image based on a pixel value of the pixel location and a saturation threshold, and computing a pixel value for each pixel location of the HDR image as a weighted sum of corresponding pixel values in the long exposure image and the short exposure image, wherein a weight applied to a pixel value of the pixel location of the short exposure image and a weight applied to a pixel value of the pixel location in the pixel long exposure image are determined based on the merging weight computed for the pixel location and responsive to motion in a scene of the long exposure image and the short exposure image.

Abstract: A method of generating a high dynamic range (HDR) image is provided that includes capturing a long exposure image and a short exposure image of a scene, computing a merging weight for each pixel location of the long exposure image based on a pixel value of the pixel location and a saturation threshold, and computing a pixel value for each pixel location of the HDR image as a weighted sum of corresponding pixel values in the long exposure image and the short exposure image, wherein a weight applied to a pixel value of the pixel location of the short exposure image and a weight applied to a pixel value of the pixel location in the pixel long exposure image are determined based on the merging weight computed for the pixel location and responsive to motion in a scene of the long exposure image and the short exposure image.

Abstract: A method of generating a high dynamic range (HDR) image is provided that includes capturing a long exposure image and a short exposure image of a scene, computing a merging weight for each pixel location of the long exposure image based on a pixel value of the pixel location and a saturation threshold, and computing a pixel value for each pixel location of the HDR image as a weighted sum of corresponding pixel values in the long exposure image and the short exposure image, wherein a weight applied to a pixel value of the pixel location of the short exposure image and a weight applied to a pixel value of the pixel location in the pixel long exposure image are determined based on the merging weight computed for the pixel location and responsive to motion in a scene of the long exposure image and the short exposure image.

Abstract: A method of generating a high dynamic range (HDR) image is provided that includes capturing a long exposure image and a short exposure image of a scene, computing a merging weight for each pixel location of the long exposure image based on a pixel value of the pixel location and a saturation threshold, and computing a pixel value for each pixel location of the HDR image as a weighted sum of corresponding pixel values in the long exposure image and the short exposure image, wherein a weight applied to a pixel value of the pixel location of the short exposure image and a weight applied to a pixel value of the pixel location in the pixel long exposure image are determined based on the merging weight computed for the pixel location and responsive to motion in a scene of the long exposure image and the short exposure image.

Abstract: A method of determining a pose of a camera is described. The method comprises analyzing changes in an image detected by the camera using a plurality of sensors of the camera; determining if a pose of the camera is incorrect; determining which sensors of the plurality of sensors are providing the most reliable image data; and analyzing data from the sensors providing the most reliable image data.

Abstract: A method for brightness and contrast enhancement includes computing a luminance histogram of a digital image, computing first distances from the luminance histogram to a plurality of predetermined luminance histograms, estimating first control point values for a global tone mapping curve from predetermined control point values corresponding to a subset of the predetermined luminance histograms selected based on the computed first distances, and interpolating the estimated control point values to determine the global tone mapping curve. The method may also include dividing the digital image into a plurality of image blocks, and enhancing each pixel in the digital image by computing second distances from a pixel in an image block to the centers of neighboring image blocks, and computing an enhanced pixel value based on the computed second distances, predetermined control point values corresponding to the neighboring image blocks, and the global tone mapping curve.

Abstract: A method of local tone mapping of a high dynamic range (HDR) image is provided that includes dividing a luminance image of the HDR image into overlapping blocks and computing a local tone curve for each block, computing a tone mapped value for each pixel of the luminance image as a weighted sum of values computed by applying local tone curves of neighboring blocks to the pixel value, computing a gain for each pixel as a ratio of the tone mapped value to the value of the pixel, and applying the gains to corresponding pixels in the HDR image. A weight for each value is computed based on distance from the pixel to the center point of the block having the local tone curve applied to compute the value and the intensity difference between the value of the pixel and the block mean pixel value.

Abstract: A method for brightness and contrast enhancement includes computing a luminance histogram of a digital image, computing first distances from the luminance histogram to a plurality of predetermined luminance histograms, estimating first control point values for a global tone mapping curve from predetermined control point values corresponding to a subset of the predetermined luminance histograms selected based on the computed first distances, and interpolating the estimated control point values to determine the global tone mapping curve. The method may also include dividing the digital image into a plurality of image blocks, and enhancing each pixel in the digital image by computing second distances from a pixel in an image block to the centers of neighboring image blocks, and computing an enhanced pixel value based on the computed second distances, predetermined control point values corresponding to the neighboring image blocks, and the global tone mapping curve.

Abstract: A method of determining a transformation is provided between an image coordinate system and an object coordinate system including: providing an object coordinate system associated with the object of interest, providing a 3D model of at least part of the object of interest, wherein the 3D model comprises 3D features, providing an N-th input depth image of at least part of the object of interest, wherein an N-th image coordinate system is associated with the N-th input depth image, providing an N-th plurality of 3D features in the N-th image coordinate system according to the N-th input depth image, estimating an N-th coarse transformation between the object coordinate system and the N-th image coordinate system according to a trained pose model and the N-th input depth image, and determining an N-th accurate transformation between the N-th image coordinate system and the object coordinate system.

Abstract: A method and device is provided for determining at least one object feature of at least one object comprised in an image. The method includes providing an input image of at least part of the at least one object, estimating a coarse pose of the at least one object according to a trained pose model and at least part of the input image, selecting a feature detection model from a plurality of feature detection models, and determining at least one object feature position of the at least one object in the input image. The selected feature detection model includes a forest data structure including at least one decision tree having leaf nodes.

Abstract: A method for brightness and contrast enhancement includes computing a luminance histogram of a digital image, computing first distances from the luminance histogram to a plurality of predetermined luminance histograms, estimating first control point values for a global tone mapping curve from predetermined control point values corresponding to a subset of the predetermined luminance histograms selected based on the computed first distances, and interpolating the estimated control point values to determine the global tone mapping curve. The method may also include dividing the digital image into a plurality of image blocks, and enhancing each pixel in the digital image by computing second distances from a pixel in an image block to the centers of neighboring image blocks, and computing an enhanced pixel value based on the computed second distances, predetermined control point values corresponding to the neighboring image blocks, and the global tone mapping curve.

Abstract: A method of local tone mapping of a high dynamic range (HDR) image is provided that includes dividing a luminance image of the HDR image into overlapping blocks and computing a local tone curve for each block, computing a tone mapped value for each pixel of the luminance image as a weighted sum of values computed by applying local tone curves of neighboring blocks to the pixel value, computing a gain for each pixel as a ratio of the tone mapped value to the value of the pixel, and applying the gains to corresponding pixels in the HDR image. A weight for each value is computed based on distance from the pixel to the center point of the block having the local tone curve applied to compute the value and the intensity difference between the value of the pixel and the block mean pixel value.

Abstract: A method of generating a high dynamic range (HDR) image is provided that includes capturing a long exposure image and a short exposure image of a scene, computing a merging weight for each pixel location of the long exposure image based on a pixel value of the pixel location and a saturation threshold, and computing a pixel value for each pixel location of the HDR image as a weighted sum of corresponding pixel values in the long exposure image and the short exposure image, wherein a weight applied to a pixel value of the pixel location of the short exposure image and a weight applied to a pixel value of the pixel location in the pixel long exposure image are determined based on the merging weight computed for the pixel location and responsive to motion in a scene of the long exposure image and the short exposure image.

Abstract: A method and apparatus for automatic white balancing of an image. The method includes retrieving scene analysis of the image, determining at least one of the type of the scene and a scene content map utilizing the scene analysis of the image, performing scene adaptive white balance, if overall scene category type is used, perform white balance by applying global R, G, B gains optimized for the global scene type, and if scene segmentation map is used, perform locally adaptive white balance by applying an R, G, B gain map optimized for each scene content.

Abstract: A method and apparatus for converting a two dimensional image or video to three dimensional image or video. The method includes segmenting objects in at least one of a two dimensional image and video, performing, in the digital processor, a depth map generation based on low-level features, performing face detection and scene classification on at least one of a two dimensional image and video, and utilizing face detection and scene classification in enhancing the depth map and for converting the at least one of a two dimensional image and video to three dimensional image and video.

Abstract: Dynamic adjustment of noise filter strengths for use with dynamic range enhancement of images is performed to produce better quality images by adapting dynamically to the image noise profile. Global and local brightness and contrast enhancement (GLBCE) is performed on a digital image to form an enhanced image. The GLBCE applies local gain values to the digital image based on local intensity values. A GLBCE gain versus intensity curve is determined for the enhanced image. A set of noise filter thresholds is adjusted in response to the GLBCE gain versus intensity curve to form a set of dynamically adjusted noise filter thresholds. The enhanced image is noise filtered using the set of dynamically adjusted noise filter thresholds to form a noise filtered enhanced image.

Abstract: A method and apparatus for enhancing at least one of video and image quality using an exposure aware scene adaptive global brightness contrast. The method includes determining if gain control is needed utilizing Gamma corrected histogram and ancillary data, if gain control is not required, computing a set of scene adaptive tone points and blending with information from histogram equalization if needed, if gain control is required, estimating gain value and utilizing the gain value in computing the gain table, and accordingly, generating a look-up table for enhancing global brightness contrast utilizing the gain table, the tone table and the information from histogram equalization.

Abstract: A method and apparatus motion triggered image stabilization. The method includes computing projection vector for at least a portion of a frame of an image using horizontal and vertical sums, performing motion estimation utilizing projection vector with the shift of the projection vector from a previous frame, performing temporal IIR filter on the motion vector, calculating the maximum horizontal and vertical motion vectors, obtaining exposure time based on the horizontal and vertical motion vectors and the gain, returning the exposure time and the gain to the auto-exposure, utilizing the returned exposure time and gain, and producing a frame with less motion blur.