Samsung Electronics Co., Ltd.

Alok Shankarlal Shukla

Kiran Nataraju

Abhijit Dey

Gaurav Khandelwal

Divyanshu Kumar

Digadari Suman

Saiksha Dhananjay Shetty

Saikat Kumar Das

Lokesh Rayasandra Boregowda

Narasimha Gopalakrishna Pai

Balvinder Singh

Pankaj Kumar Bajpai

Sathish Chalasani

Karthik Srinivasan

Karthik Narayanan

Girish R Kulkarni

Jin-hee Na

Woojhon Choi

Insung Hwang

Wonjoon Do

Manoj Kumar

Jaesung Choi

Pradeep Kumar Sindhagatta Krishnappa

Pranav Prakash Deshpande

Venkat Ramana Peddigari

Prajit Sivasankaran Nair

Green Rosh K S

Pyo-jae Kim

Raghavendra Kalose Mathsyendranath

Girish Kulkarni

Mahesh Putane Jagadeeshrao

Sanket Sambhajirao Deshmukh

Pradeep Choudhary

Kasireddy Viswanatha Reddy

Keyur Ruganathbhai Ranipa

Abhishek Somani

Venkatesh Ambati

Saketh Sharma

Sai Kumar Reddy Manne

Nitin Kumar Singh

Rishikesh Jha

Shashavali Doodekula

Siddharth Deepak Roheda

Divay Bhutani

Pawan Prasad Bindigan Hariprasanna

Nitin Kamboj

Manoj Kumar Marram Reddy

Prasanna Kumar Avanigadda

Madhupa Chowdhury

Ajay Vijayvargiya

A method for performing multi-functional image restoration by an electronic device with a trained Machine Learning (ML) model is provided. The method includes receiving an image and determining channels of the image, and determining whether a number of restructuring needed for the channels is one. When the restructuring needed for the channels not one, then the method includes restructuring each channel into a first channel set, generating first inferences of the image corresponding to each channel by feeding the first channel set to the trained ML model, and generating a final inference image by combining the first inferences. When the number of restructuring needed for the channels is one, then the method includes restructuring the channels into a second channel set, and generating a second inference of the image by feeding the second channel set to the trained ML model.

Method and electronic device for multi-functional image restoration

A method for removing an artifact in a high resolution image by an electronic device is provided. The method includes receiving the high resolution image comprising the artifact. Further, the method includes downscaling the high resolution image into a plurality of lower resolution images. Further, the method includes removing the artifact from the plurality of lower resolution images by applying at least one first machine learning model from a plurality of machine learning models on the plurality of lower resolution images. Further, the method includes generating a high resolution image free from the artifact by applying at least one second machine learning model from the plurality of machine learning models on an output from the at least one first machine learning model. The output from each of the machine learning model comprises a low resolution image free from the artifact.

Method and electronic device for removing artifact in high resolution image

A method performed by an electronic device for generating a slow motion video includes obtaining plural image frames captured at a frame rate from a camera of the electronic device, detecting motion information in a first image frame from among the plural image frames, and performing an interpolation operation using one or more image frames from among the plural image frames. The one or more image frames are image frames obtained during a predetermined time after the first image frame in which the motion information is detected. A second image frame obtained before the first image frame in which the motion information is detected is discarded from the electronic device. A third image frame obtained after the predetermined time from the first image frame in which the motion information is detected is discarded from the electronic device.

Method and system for recording a super slow motion video in a portable electronic device

An electronic device includes a UDC and a UDC controller configured to determine an optimal number of frames required to be captured for a scene to compensate at least one parameter to optimize an output media using the UDC, obtain a multi-frame fusion media by performing at least one multi-frame fusion on the determined optimal number of frames, perform a light source spread correction on the multi-frame fusion media, and optimize the output media based on the light source spread correction on the multi-frame fusion media.

Method and electronic device for capturing media using under display camera

A method and an apparatus for capturing a high quality dynamic image by setting a different row-wise exposure value when capturing a scene are provided. The dynamic image capturing method includes: generating an image by pre-capturing a scene via an event sensor; generating event data from the image; determining a row-wise exposure value of the image based on the event data; and determining a row-wise readout priority order of the image based on the row-wise exposure value of the image.

Method and apparatus for dynamic image capturing based on motion information in image

A method for processing image frames, and an electronic device are provided. The method includes receiving image frames captured by an image sensor at a first frame rate and storing the received image frames in a memory. A change is detected in the stored image frames and an image frame is interpolated between the stored image frames after detecting the change. The interpolated image is stored in the memory.

Methods and systems for reconstructing a high frame rate high resolution video in a Bayer domain, when an imaging device is set in a Flexible Sub-Sampled Readout (FSR) mode are described. A method provides the FSR mode, which utilizes a multiparty FSR mechanism to spatially and temporally sample the full frame Bayer data. The multi parity FSR utilizes a zigzag sampling that assists reconstruction of motion compensated artifact free high frame rate high resolution video with full frame size. The method includes reconstructing the high frame rate high resolution video using the plurality of parity fields generated. The reconstruction is based on a FSR reconstruction mechanism that can be a pre-Image Signal Processor (ISP) FSR reconstruction or a post-ISP FSP reconstruction based on bandwidth capacity of an ISP used by the imaging device.

Methods and systems for reconstructing a high frame rate high resolution video

An electronic device and a method for human segmentation in an image are provided. The method includes obtaining the image comprising at least one human, performing face detection to detect the human in the image, generating a first human segmentation from the image by comparing a pre-defined full human body template and the detected human, generating a second human segmentation from the image, by inputting the image to an artificial intelligence trained model and obtaining a composite human segmentation representing the detected human by using both of the first human segmentation and the second human segmentation.

Electronic device and method for automatic human segmentation in image

A method and a system for recording a Super Slow Motion (SSM) video in a portable electronic device are provided. A SSM video recording system detects presence of motion in the image frames captured by the image capturing device. Upon detecting the presence of motion, the SSM video recording system generates a trigger, subsequent to which, a first and fourth set of image frames for performing a frame skipping mechanism, and a second and third set of image frames for performing an interpolation mechanism are selected. The image frames of desired frame rate generated by performing the frame skipping mechanism and the interpolation mechanism are transmitted to an encoder in an order, for encoding and recording. The method and system allow SSM even in mid-tier and low-tier models of smartphones, without the need of expensive specialized image sensors.

A method for generating video data using an imaging device is provided. The method includes capturing, by a first sensor of the imaging device, a first set of sub-sampled monochrome frames, capturing, by a second sensor of the imaging device, a second set of sub-sampled color frames, reconstructing one or more high resolution monochrome frames using the first set of sub-sampled monochrome frames, and generating one or more high speed high resolution color frames based on the second set of sub-sampled color frames and the reconstructed one or more high resolution monochrome frames.

Method and apparatus for capturing video data

A method and an electronic device for producing a composite image are provided. The method includes receiving visible image data and near infrared (NIR) image data from a composite sensor, determining whether at least one portion of the NIR image data having a level of detail greater than or equal to a threshold, and generating a composite image by fusing the visible image data with the at least one portion of the NIR image data based on the determination and storing the composite image in a memory.

Method and electronic device for producing composite image

An electronic device and a method for automatically displaying an indication in a multi-dimensional media in the electronic device are provided. The method includes receiving the multi-dimensional media at the electronic device, displaying a first view port of the multi-dimensional media on a screen of the electronic device, detecting at least one region of interest (ROI) in the multi-dimensional media based on plurality of parameters, and displaying an indication indicating at least one second view port of the multi-dimensional media on the screen. The second view port includes at least one ROI.

Method for providing indication in multi-dimensional media in electronic device

A method and an apparatus for generating a composite image in an electronic device are provided. The method includes identifying a first image element of a first event from first images successively captured by a first image sensor of the electronic device, and identifying a second image element of a second event from second images successively captured by a second image sensor of the electronic device, the first images and the second images being simultaneously captured. The method further includes combining the first image element with the second image element based on a synchronization parameter to generate the composite image.

Method and apparatus for generating composite image in electronic device

A method and a device to compose an image by eliminating one or more moving objects in a scene being captured are provided. The method includes capturing plurality of images, generating a background image with a plurality of stationary objects after aligning the plurality of captured images, selecting a base image from a plurality of the aligned images, wherein the base image is selected based on a highest similarity measure with the background image, identifying the at least one moving object in the base image, and eliminating said identified at least one moving object in the base image to compose said image.

Method and device to compose an image by eliminating one or more moving objects

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Bengaluru, India

Alok Shankarlal Shukla