Abstract: A method of automatically focusing a projector in a projection system is provided that includes projecting, by the projector, a binary pattern on a projection surface, capturing an image of the projected binary pattern by a camera synchronized with the projector, computing a depth map from the captured image, and adjusting focus of the projector based on the computed depth map.

Abstract: Wide dynamic range depth imaging in a structured light device is provided that improves depth maps for scenes with a wide range of albedo values under varying light conditions. A structured light pattern, e.g., a time-multiplexed structured light pattern, is projected into a scene at various projection times and a camera captures images of the scene for at least the same exposure times as the projection times. A depth image is computed for each of the projection/exposure times and the resulting depth images are combined to generate a composite depth image.

Abstract: A method for estimating illumination of an image captured by a digital system is provided that includes computing a feature vector for the image, identifying at least one best reference illumination class for the image from a plurality of predetermined reference illumination classes using the feature vector, an illumination classifier, and predetermined classification parameters corresponding to each reference illumination class, and computing information for further processing of the image based on the at least one best reference illumination class, wherein the information is at least one selected from a group consisting of color temperature and white balance gains.

Abstract: A method of noise filtering of a digital video sequence is provided that includes computing a motion image for a frame, wherein the motion image includes a motion value for each pixel in the frame, and wherein the motion values are computed as differences between pixel values in a luminance component of the frame and corresponding pixel values in a luminance component of a reference frame, applying a first spatial noise filter to the motion image to obtain a final motion image, computing a blending factor image for the frame, wherein the blending factor image includes a blending factor for each pixel in the frame, and wherein the blending factors are computed based on corresponding motion values in the final motion image, generating a filtered frame, wherein the blending factors are applied to corresponding pixel values in the reference frame and the frame, and outputting the filtered frame.

Abstract: A method and apparatus for estimating stereo misalignment using modified affine or perspective model. The method includes dividing a left frame and a right frame into blocks, comparing horizontal and vertical boundary signals in the left frame and the right frame, estimating the horizontal and the vertical motion vector for each block in a reference frame, selecting a reliable motion vectors from a set of motion vectors, dividing the selected block into smaller features, feeding the data to an affine or a perspective transformation model to solve for the model parameters, running the model parameters through a temporal filter, portioning the estimated misalignment parameters between the left frame and right frame, and modifying the left frame and the right frame to save some boundary space.

Abstract: A method for automatic convergence of stereoscopic images is provided that includes receiving a stereoscopic image, generating a disparity map comprising a plurality of blocks for the stereoscopic image, clustering the plurality of blocks into a plurality of clusters based on disparities of the blocks, selecting a cluster of the plurality of clusters with a smallest disparity as a foreground cluster, determining a first shift amount and a first shift direction and a second shift amount and a second shift direction based on the smallest disparity, and shifting a left image in the stereoscopic image in the first shift direction by the first shift amount and a right image in the stereoscopic image in the second shift direction by the second shift amount, wherein the smallest disparity is reduced.

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 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 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: A method for calibrating automatic white balance (AWB) is provided that includes using a plurality of references for AWB that include color temperature references, wherein an AWB failure is detected in an image, generating a scene prototype reference based on the image, and adding the generated scene prototype reference to the references for AWB. A method for calibrating AWB is provided that includes selecting an image as a scene prototype, wherein the selected image was captured by a second imaging sensor different from a first imaging sensor, transforming the selected image into a scene prototype image for the first imaging sensor, generating a scene prototype reference using the scene prototype image for the first imaging sensor, and adding the generated scene prototype reference to references for AWB that include color temperature references.

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: Methods for automatic focus in a stereographic imaging device that includes two imaging sensor systems are provided. Focus searches are executed on both imaging sensor systems to determine optimal focused lens positions for each. The focus searches may be executed currently or sequentially, and may be at differing lens position granularities. Focal scores and spatial locations, i.e., the locations of focus regions, may be shared between the imaging sensor systems to coordinate the focus searches. Touchscreen coordinates may also be used to coordinate the focus searches.

Abstract: Image noise reduction filtering by low-pass/high-pass filtering to get a hierarchical representation, modifying coefficients in each hierarchy level for noise suppression, and the modified level combination to yield a noise-filtered image. The noise suppression within levels preserves edges which the representation preserves.

Abstract: Methods for automatic focus in a stereographic imaging device that includes two imaging sensor systems are provided. Focus searches are executed on both imaging sensor systems to determine optimal focused lens positions for each. The focus searches may be executed currently or sequentially, and may be at differing lens position granularities. Focal scores and spatial locations, i.e., the locations of focus regions, may be shared between the imaging sensor systems to coordinate the focus searches. Touchscreen coordinates may also be used to coordinate the focus searches.

Abstract: A method and apparatus for reducing convergence accommodation conflict. The method includes estimating disparities between images for different lens, analyzing the estimated disparities, selecting a point of convergence, determining the amount of shift relating to the convergence point selected, and performing adjustment to the disparity to maintain a disparity value below a threshold.

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.

Abstract: A method and apparatus for estimating stereo misalignment using modified affine or perspective model. The method includes dividing a left frame and a right frame into blocks, comparing horizontal and vertical boundary signals in the left frame and the right frame, estimating the horizontal and the vertical motion vector for each block in a reference frame, selecting a reliable motion vectors from a set of motion vectors, dividing the selected block into smaller features, feeding the data to an affine or a perspective transformation model to solve for the model parameters, running the model parameters through a temporal filter, portioning the estimated misalignment parameters between the left frame and right frame, and modifying the left frame and the right frame to save some boundary space.

Abstract: A method of processing a digital video sequence is provided that includes estimating compensated motion parameters and compensated distortion parameters (compensated M/D parameters) of a compensated motion/distortion (M/D) affine transformation for a block of pixels in the digital video sequence, and applying the compensated M/D affine transformation to the block of pixels using the estimated compensated M/D parameters to generate an output block of pixels, wherein translational and rotational jitter in the block of pixels is stabilized in the output block of pixels and distortion due to skew, horizontal scaling, vertical scaling, and wobble in the block of pixels is reduced in the output block of pixels.

Abstract: A digital camera function, such as can be implemented in a cellular telephone handset, and that includes automated segmentation of foreground subjects in acquired digital photos and images. Successive images are captured by the digital camera function at different flash exposure levels, for example using existing light only and using flash exposure. After alignment and registration of the images, luminance difference values in the two images are determined for each pixel, and the luminance difference values compared against a threshold value on a pixel-by-pixel basis. Those pixels with luminance difference values exceeding the threshold are segmented from the image as foreground subjects.

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.