Samsung Electronics Co., Ltd.

Gal Bitan

Roy Yam

Gershi Koltun

Igal Avishai

Amit Eisenberg

Shay Hamami

Haim Azaria

Tal Bernstein

Woo-Shik Kim

Yoel Yaffe

Min Sun Keel

Soongeun Jang

Oded Monzon

Shy Hamami

Guy Horowitz

Yoav Piepsh

Ilya Romm

Yoram Furth

Lena Grechikhin

Tal Michael Feld

Taeer Weiss

Shahaf Duenyas

Methods and apparatuses for correcting bad image pixels are described. The described sensor-independent image processing techniques leverage one or more dynamic dictionaries of learned filters for bad pixel correction (e.g., where a camera leverages such dictionaries to efficiently identify filters to accurately adjust and correct bad pixel values). For example, a dictionary may store filters that are learned offline (via a self-supervised learning algorithm implemented at a server using known images and ground truth bad pixel correction values). To select a filter for a bad pixel correction operation, a camera may encode an image patch surrounding a bad pixel (into an encoded patch descriptor) and search the dictionary for a matching patch descriptor key. The camera may then apply the filter (value) corresponding to the searched patch descriptor (key) of the dictionary to the image patch to correct the bad pixel and generate a corrected output image.

Learning based bad pixel correction

Provided is an apparatus for obtaining an image includes an image sensor and a signal processing unit that includes a demosaicing unit configured to reconstruct a green signal to have a full pixel resolution by using the input image, a sharpening filter unit configured to generate a first image by sharpening the reconstructed green signal for each preset direction, a direction image generation unit which generates a second image by removing a base band and extracting only a detail band, a gray detection unit configured to detect a gray region of the white balance-processed input image, an edge detection unit configured to detect an edge direction of the white balance-processed input image, and a selection unit configured to generate a third image by blending the first image and the second image, based on the detected gray region and the detected edge direction.

Apparatus and method for obtaining image employing color separation lens array

A pixel array of an image sensor includes a plurality of color filter array (CFA) cells. Each of the plurality of CFA cells includes first, second, third, and fourth CFA blocks. Each of the first and second CFA blocks includes a plurality of pixels to sense light of a first color. Most pixels of the third CFA block are configured to sense the second color and the third CFA block includes at least one first pixel to sense the first light. Most pixels of the fourth CFA block are configured to sense a third color of light and the fourth CFA block includes at least one second green pixel to sense the first light.

Color filter array for de-mosaicing and binning

In a method for time-of-flight (ToF) based measurement, a scene is illuminated using a ToF light source modulated at a first modulation frequency F. While the light is modulated using F, depths are measured to respective surface points within the scene, where the surface points are represented by a plurality of respective pixels. At least one statistical distribution parameter is computed for the depths. A second modulation frequency Fhigher than Fis determined based on the at least one statistical distribution parameter. The depths are then re-measured using Fto achieve a higher depth accuracy.

Time-of-flight depth measurement using modulation frequency adjustment

A method of controlling power usage in an image signal processor includes measuring an actual percentage of flat pixels in a digital image, adjusting a percentage threshold of flat pixels in the digital image, based on the measured actual percentage of flat pixels in the digital image; and processing the digital image by the image signal processor based on the percentage threshold of flat pixels. The percentage threshold of flat pixels is adjusted to reduce power used by the image signal processor in processing the digital image.

Closed loop dynamic ISP throttling

A method performed with an image sensor having a pixel array. At least one frame of a scene may be obtained using the pixel array. At least one region of interest (ROI) is identified within the frame. Subsequent frames of the scene are obtained, which involves controlling the pixel array to perform high resolution imaging with respect to the at least one ROI and low resolution imaging using analog binning with respect to remaining regions of the frames.

Image sensor employing varied intra-frame analog binning

A method for time-of-flight (ToF) guided down-up sampling includes calculating a guide function from a full resolution output of a ToF sensor, downsampling the full resolution output by a predetermined scaling factor, calculating a downsampled depth data from the downsampled output and upsampling the downsampled depth data to full resolution using the full resolution guide function.

Time-of-flight down-up sampling using a compressed guide

A method for down-up sampling of image sensor data includes the steps of down sampling green pixels in a super Bayer pattern of image sensor data, where a decimation factor of the downsampling corresponds to a size of a color cluster in the super Bayer pattern, where two green pixels that are those closest to a non-green pixel cluster remain in each green cluster after downsampling, and wherein each non-green pixel cluster is bordered by four downsampled green pixels, and up sampling non-green color pixels in a non-green cluster from the remaining green pixels that are closest to the non-green cluster by a bilinear interpolation of each non-green pixel with respect to the closest remaining green pixels, where the up sampling of the non-green color pixels is guided by a compressed array that corresponds to the image sensor data.

Image sensor down-up sampling using a compressed guide

A time of flight (ToF) sensor includes: a first pixel including a first photogate to receive light reflected by an object and generate a first phase signal, and a second photogate to generate a second phase signal having a phase difference of 180 degrees with respect to the first phase signal; a second pixel including a third photogate to receive the reflected light and generate a third phase signal different from the first phase signal and a fourth photogate to generate a fourth phase signal having a phase difference of 180 degrees with respect to the third phase signal; a first signal output unit to output the first and second phase signals; and a second signal output unit to output the third and fourth phase signals, wherein the first, second, third and fourth photogates output the first to fourth phase signals during a frame period.

Time of flight sensor, a three-dimensional imaging device using the same, and a method for driving the three-dimensional imaging device

An HDR image sensor supporting LED Flicker Mitigation to reduce Motion Blur and a method of operating same are provided. A timing controller circuit generates at least one control signal that controls an operation of the image sensor. A split-photodiode (PD) pixel includes at least two or more photodiodes that may be independently exposed to one or more bursts of light from a light source. A first photodiode of the two or more photodiodes has a first exposure period that is longer in duration than a second exposure period of a second photodiode of the two or more photodiodes. The second photodiode performs a fragmented exposure operation in which a plurality of exposure periods of the second photodiode are shorter in duration than the first exposure period of the first photodiode, and include both continuous and fragmented exposure periods to capture the one or more bursts of light.

HDR image sensor with LFM and reduced motion blur

HDR image sensor with LFM and reduced Motion Blur

A method for calculating disparity in a pair of images includes receiving a first image of a scene and designating the first image as a master image. A second image of the scene is received, and the second image is designated as a slave image. The master image is binarized to produce a binarized master image. The slave image is binarized to produce a binarized slave image. A matching cost associated with matching each pixel within the binarized master image with a corresponding set of candidate pixels within the binarized slave image is calculated. A probability density function is created based on the calculated matching costs associated with each pixel within the binarized master image. The created probability density function is used to produce a disparity for the master image and the slave image and to produce a confidence for the produced disparity.

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Petach-Tikva, Israel

Gal Bitan