Abstract: Electronic devices, methods, and program storage devices for achieving smooth zooming operations during video capture are disclosed. In particular, smooth zooming may be desirable during video capture operations that involve a single image capture device and/or transitioning between two or more distinct image capture devices, e.g., having different optical and/or zooming properties, during the video capture. When video zooming is done abruptly, it can lead to an unpleasant user experience. The techniques described herein to improve the smoothness of zooming operations include: the use of longer zoom “ramps” for image capture devices; the “early” transitioning between image capture devices during video capture; and the performance of additional “digital zoom smoothing-aware” video image stabilization operations. The embodiments described herein also provide for a more consistent user experience between video streaming (i.e., “preview”) modes and the recorded (i.e.

Abstract: A construction building equipment includes hanging pedestals, sleeve frames, hydraulic cylinders, upper reversing boxes, lower reversing boxes and track columns. The multiple hanging pedestals are fixed on an outer side of a shear wall of an external wall. The sleeve frames and the track columns are clamped on the hanging pedestals. The sleeve frames are clamped on outer sides of the track columns. The lower reversing boxes are fixed at upper ends of the sleeve frames. The hydraulic cylinders are connected with the upper reversing boxes and the lower reversing boxes. Side surfaces of the track columns are provided with pane holes for cooperative climbing of the upper reversing boxes and the lower reversing boxes. Upper ends of the track columns are fixedly connected with a top platform. Hangers and formworks are suspended on the top platform through booms.

Abstract: A construction building equipment includes hanging pedestals, sleeve frames, hydraulic cylinders, upper reversing boxes, lower reversing boxes and track columns. The multiple hanging pedestals are fixed on an outer side of a shear wall of an external wall. The sleeve frames and the track columns are clamped on the hanging pedestals. The sleeve frames are clamped on outer sides of the track columns. The lower reversing boxes are fixed at upper ends of the sleeve frames. The hydraulic cylinders are connected with the upper reversing boxes and the lower reversing boxes. Side surfaces of the track columns are provided with pane holes for cooperative climbing of the upper reversing boxes and the lower reversing boxes. Upper ends of the track columns are fixedly connected with a top platform. Hangers and formworks are suspended on the top platform through booms.

Abstract: A method of transforming an N-bit raw wide dynamic range (WDR) Bayer image to a K-bit raw red-green-blue (RGB) image wherein N>K is provided that includes converting the N-bit raw WDR Bayer image to an N-bit raw RGB image, computing a luminance image from the N-bit raw RGB image, computing a pixel gain value for each luminance pixel in the luminance image to generate a gain map, applying a hierarchical noise filter to the gain map to generate a filtered gain map, applying the filtered gain map to the N-bit raw RGB image to generated a gain mapped N-bit RGB image, and downshifting the gain mapped N-bit RGB image by (N?K) to generate the K-bit RGB image.

Abstract: A method, apparatus and a surround view camera system for determining the optimal seam for a surround view camera system. The method includes determining the corrected side view image at bird-eye perspective, generating a cost map for overlapping region, finding a minimum cost seam for each overlapping region, computing weight based on distance to the seam, if blending of the pixel, and blending the pixel, synthesizing composite view, and generating a composite view image.

Abstract: A method, apparatus and a system multi-camera image processing method. The method includes performing geometric alignment to produce a geometric output, performing photometric alignment to produce a photometric output and blending output, using data from the geometric alignment and the photometric alignment for performing synthesis function for at least one of blending and stitching images from the multi-cameras, and displaying an image from the synthesis function.

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, apparatus and a surround view camera system. The method includes extracting block samples from at least one of a composite view geometric LUT, input fish-eye image and view overlapping region, selecting sample inliers from the extracted block samples, estimating optimal color gain for the selected block samples, performing refined adjustment based on the estimated color gain and applying color transform, and producing a composite surround view image.

Abstract: A first depth map is generated in response to a stereoscopic image from a camera. The first depth map includes first pixels having valid depths and second pixels having invalid depths. In response to the first depth map, a second depth map is generated for replacing at least some of the second pixels with respective third pixels having valid depths. For generating the second depth map, a particular one of the third pixels is generated for replacing a particular one of the second pixels. For generating the particular third pixel, respective weight(s) is/are assigned to a selected one or more of the first pixels in response to value similarity and spatial proximity between the selected first pixel(s) and the particular second pixel. The particular third pixel is computed in response to the selected first pixel(s) and the weight(s).

Abstract: A method of transforming an N-bit raw wide dynamic range (WDR) Bayer image to a K-bit raw red-green-blue (RGB) image wherein N>K is provided that includes converting the N-bit raw WDR Bayer image to an N-bit raw RGB image, computing a luminance image from the N-bit raw RGB image, computing a pixel gain value for each luminance pixel in the luminance image to generate a gain map, applying a hierarchical noise filter to the gain map to generate a filtered gain map, applying the filtered gain map to the N-bit raw RGB image to generated a gain mapped N-bit RGB image, and downshifting the gain mapped N-bit RGB image by (N?K) to generate the K-bit RGB image.

Abstract: A method of transforming an N-bit raw wide dynamic range (WDR) Bayer image to a K-bit raw red-green-blue (RGB) image wherein N>K is provided that includes converting the N-bit raw WDR Bayer image to an N-bit raw RGB image, computing a luminance image from the N-bit raw RGB image, computing a pixel gain value for each luminance pixel in the luminance image to generate a gain map, applying a hierarchical noise filter to the gain map to generate a filtered gain map, applying the filtered gain map to the N-bit raw RGB image to generated a gain mapped N-bit RGB image, and downshifting the gain mapped N-bit RGB image by (N?K) to generate the K-bit RGB image.

Abstract: A method, apparatus and a system multi-camera image processing method. The method includes performing geometric alignment to produce a geometric output, performing photometric alignment to produce a photometric output and blending output, using data from the geometric alignment and the photometric alignment for performing synthesis function for at least one of blending and stitching images from the multi-cameras, and displaying an image from the synthesis function.

Abstract: A method, apparatus and a surround view camera system for determining the optimal seem for a surround view camera system. The method includes determining the corrected side view image at bird-eye perspective, generating a cost map for overlapping region, finding a minimum cost seam for each overlapping region, computing weight based on distance to the seam, if blending of the pixel, and blending the pixel, synthesizing composite view, and generating a composite view image.

Abstract: A method, apparatus and a surround view camera system. The method includes extracting block samples from at least one of a composite view geometric LUT, input fish-eye image and view overlapping region, selecting sample inliers from the extracted block samples, estimating optimal color gain for the selected block samples, performing refined adjustment based on the estimated color gain and applying color transform, and producing a composite surround view image.

Abstract: A device stores a list of geographic regions and respective sets of device parameters for achieving target visual characteristics thereof. One of the geographic regions is selected. In response to the selected geographic region's respective set of device parameters, the device automatically adapts for achieving the selected geographic region's target visual characteristics in the device's enhancement of images. At least one of the images is enhanced with the adapted device.

Abstract: A camera points in a first direction and is positioned within borders of a screen of a display device. The screen faces in a second direction that is substantially parallel to the first direction. While the camera views a scene, the screen displays an image of the viewed scene. While the screen displays the image, the image is written for storage on a computer-readable medium.

Abstract: A method of transforming an N-bit raw wide dynamic range (WDR) Bayer image to a K-bit raw red-green-blue (RGB) image wherein N>K is provided that includes converting the N-bit raw WDR Bayer image to an N-bit raw RGB image, computing a luminance image from the N-bit raw RGB image, computing a pixel gain value for each luminance pixel in the luminance image to generate a gain map, applying a hierarchical noise filter to the gain map to generate a filtered gain map, applying the filtered gain map to the N-bit raw RGB image to generated a gain mapped N-bit RGB image, and downshifting the gain mapped N-bit RGB image by (N?K) to generate the K-bit RGB image.

Abstract: A method for calibrating automatic white balance (AWB) in a digital system is provided that includes capturing an image of a test target under a natural lighting condition, generating a first color temperature reference from the captured image, and outputting AWB configuration data for the digital system, wherein the AWB configuration data comprises the first color temperature reference and a second color temperature reference generated using the test target under simulated lighting conditions. A method for calibrating automatic white balance (AWB) in a digital system comprising a first imaging sensor is provided that includes receiving a reference for AWB that was generated using an image captured using a second imaging sensor, and compensating a histogram reference into a histogram reference for AWB for the first imaging sensor in the digital system based on R, G, B adjustment values from the second imaging sensor to the first imaging sensor.

Abstract: In response to an image, a likelihood of flicker within the image is estimated. In response to the estimated likelihood, references are selected from among first and second sets of references. The first set of references are responsive to a first set of reference images captured under particular illumination. The second set of references are responsive to a second set of reference images captured under fluorescent illumination. In response to the selected references, one or more gains are generated for enhancing white balance of the 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.