Samsung Electronics Co., Ltd.

Roee Sfaradi

Doron Sabo

Omry Sendik

Amit Eisenberg

Ju Young Lee

German Voronov

Eugene Fainstain

Evgeny Artyomov

Oded Monzon

Assaf Tzabari

Artem Zinevich

Stas Dubinchik

Yarden Sharabi

Sapir Kontente

Shachar Praisler

A method for processing images acquired by a multi-spectral RGB-NIR (red/green/blue/near infra-red) sensor includes receiving a RGB-NIR digital image from a multi-spectral RGB-NIR sensor, interpolating an NIR contribution to each R, G and B pixel value, wherein an NIR image is obtained, subtracting the NIR contribution from each R, G and B pixel value in the RGB-NIR digital image wherein a decontaminated RGB-NIR image is obtained, constructing a red, green and blue (RGB) Bayer image from the decontaminated RGB-NIR image, and processing the Bayer image wherein a full color image is obtained. The RGB-NIR digital image includes red (R) pixels, green (G) pixels, blue (B) pixels, and NIR pixels, and every other row in the RGB-NIR digital image includes NIR pixels that alternate with green pixels, and every other row in the RGB-NIR digital image includes green pixels that alternate with red and blue pixels.

RGB-NIR processing and calibration

Systems and methods for setting the white balance of an image are described. Embodiments of the systems and methods may receive image data comprising a plurality of exposures, generate a plurality of white balance values based on merge information from a high dynamic range (HDR) merge of the exposures, and adjust a white balance of each pixel of the image data based on the white balance values.

Leveraging HDR sensors for handling mixed illumination auto white balance

A method of rectifying stereo images includes providing a plurality of pairs of sets of keypoints extracted from a pair of current stereo images and from a pair of previous stereo images wherein each pair of stereo images includes a left image and a right image respectively obtained from a left camera and a right camera; providing a plurality of pairs of sets of next-choice-match points extracted from the pair of current stereo images and the pair of previous stereo images; finding one or more anchor points in a left previous image; finding a right linking point which is the corresponding keypoint in the right previous image, and a left linking point which is the corresponding keypoint in the left current image; finding a closing point; and calculating a cost from the right linking point, the left linking point, and the closing point.

Rectifying a sequence of stereo images

Exemplary embodiments of the invention as described herein generally provide for detecting the displacement of feature(s) within a visual image in cases where pattern matching fails due to the existence of aperture(s) caused for example by external condition(s) encountered in recording such an image over time. Technique(s) are disclosed for detecting the difference between displacement of a geometric feature of an object appearing within an image (e.g., an edge or smooth surface) that has an aperture and another feature (e.g., a corner) that does not since it is not symmetrically invariant.

Content aware visual image pattern matching

A method and apparatus performing scene-adaptive auto-focusing for image capture with a variable-focus lens. The array of color pixels includes a array of half-covered light sensors to obtain lens-focus state information. The exposure time of the plurality of partially-covered light sensors is dynamically selected as long-exposure or short-exposure, based upon a current measurement of a property (e.g., brightness, or color-specific brightness) of a selected region of interest within a scene to be captured by the array. Then, focus state information corresponding to the selected region of interest is obtained by capturing light from the selected region of interest with first and second partially-covered light sensors. The exposure time of the partially-covered light sensors can be changed based on whether the brightness is greater than a predetermined threshold value.

Circuit and method providing wide dynamic-range operation of auto-focus(AF) focus state sensor elements, digital imaging device, and computer system including same

An image processing method includes: receiving image data of a Bayer format comprising red color information, green color information, and blue color information, generating image data of a modified Bayer format by combining the green color information with the red color information and combining the green color information with the blue color information while downscaling the image data of the Bayer format to a target resolution, denoising the image data of the modified Bayer format, and generating RGB image data by demosaicing the denoised image data of the modified Bayer format.

Image processing method, image signal processor, and image processing system including the same

An image processing method includes the operations of receiving N&#xd7;N raw data from an N&#xd7;N sub pixel array including a plurality of first exposure pixels and second exposure pixels having different exposure times, respectively; obtaining a difference value between a value obtained by normalizing an interpolated value of the first exposure pixels and an interpolated value of the second exposure pixels for each channel in the N&#xd7;N sub pixel array based on the N&#xd7;N raw data; setting a mismatching value to a maximum value among difference values obtained for the respective channels; and setting a corrected value of a central pixel in the N&#xd7;N sub pixel array based on the N&#xd7;N raw data and based on the mismatching value and a threshold value.

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Nes Ziona, Israel

Roee Sfaradi