Csr Technology Inc.

Zoran Corporation

Artemy Baxansky

Meir Tzur

Victor Pinto

Yonatan Shlomo Simson

Guy Rapaport

A system and method for capturing images is provided. In the system and method, preview images are acquired and global local and local motion are estimated based on at least a portion of the preview images. If the local motion is less than or equal to the global motion, a final image is captured based at least on an exposure time based on the global motion. If the local motion is greater than the global motion, a first image is captured based on at least a first exposure time and at least a second image is captured based on at least one second exposure time less than the first exposure time. After capturing the first and second images, global motion regions are separated from local motion regions in the first and second images, and the final image is reconstructed at least based on the local motion regions.

Image enhancement based on multiple frames and motion estimation

Methods for estimating the point spread function (PSF) of a motion-blurred image are disclosed and claimed. In certain embodiments, the estimated PSF may be used to compensate for the blur caused by hand-shake without the use of an accelerometer or gyro. Edge spread functions may be extracted along different directions from straight edges in a blurred image and combined to find the PSF that best matches. In other embodiments, the blur response to edges of other forms may similarly be extracted, such as corners or circles, and combined to find the best matching PSF. The PSF may then be represented in a parametric form, where the parameters used are related to low-order polynomial coefficients of the angular velocity vx(t) and vy(t) as a function of time.

Estimation of point spread functions from motion-blurred images

Methods for estimating illumination parameters under flickering lighting conditions are disclosed. Illumination parameters, such as phase and contrast, of a intensity-varying light source may be estimated by capturing a sequence of video images, either prior to or after a desired still image to be processed. The relative average light intensities of the adjacently-captured images are calculated and used to estimate the illumination parameters applicable to the desired still image. The estimated illumination parameters may be used to calculate the point spread function of a still image for image de-blurring processing. The estimated illumination parameters may also be used to synchronize the exposure timing of a still image to the time when there is the most light, as well as for use in motion estimation during view/video modes.

Image processing under flickering lighting conditions using estimated illumination parameters

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.

Depth from defocus calibration

A device for color shading correction is provided. Local color matching is performed as follows. For each pixel of the image that is being color matched, the RGB value is treated as a one-by-three matrix, which is multiplied by a three-by-three matrix that is generated during factory calibration. The matrix product is a one-by-three matrix that is used as the RGB value for the pixel in the color matched image.

Apparatus, method, and manufacture for correcting color shading in CMOS image sensors

A camera with auto-focusing performs multiple iterations in which the distance from the camera to an object is estimated for the purpose of auto-focusing the camera. Each estimate is made using depth-from-defocus with at least two images used to make the estimate. When the two images are taken, the camera parameters are different. For example, the focus position, aperture, or zoom may be different between the two images. In each subsequent iteration, the previous estimate of distance from the camera to the object is used so that the parameter varied (focus position or zoom) is closer to that corresponding to the estimated distance from the camera to the object, so that the estimated distance is closer to the actual distance in each iteration.

Apparatus, method, and manufacture for iterative auto-focus using depth-from-defocus

A method of processing an image includes obtaining the image; determining a point spread function for the image; applying a filter, based on the point spread function, to at least a portion of the image to form a filtered image; and generating a processed image by blending the filtered image with the image or another filtered image, wherein a first portion of the processed image is generated using a different amount of blending of the filtered image with the image or other filtered image than is used for a second portion of the processed image.

Method, apparatus, and system for reducing blurring in an image

A method of processing an image includes determining at least one point spread function for the image. For each point spread function, the image, or at least a portion of the image, is filtered using at least one filter based on that point spread function to generate a corresponding filtered image for each filter. If only a single point spread function is determined then a plurality of different filters are used to individually filter the image, or at least a portion of the image, to generate a plurality of different filtered images. At least one quality metric is determined for each of the filtered images. A final filtered image is selected from the filtered images based on the at least one quality metric for each of the filtered images.

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Nesher, Israel

Artemy Baxansky