Abstract: A method for generating metadata pertaining to a RAW frame includes selecting an input frame from a captured RAW frame, a plurality of frames obtained by processing the captured RAW frame, and a scaled RAW frame, selecting identified salient regions in an output frame, constructed from the captured RAW frame, based on errors between regions of the input frame and a corresponding reconstruction of the region of the input frame from the identified salient regions in the output frame, obtaining a plurality of reconstructed frames, reconstructed from a plurality of blocks of each salient region, corresponding to a plurality of regions of the input frame, and generating metadata for reconstructing the captured RAW frame by encoding a plurality of errors between the plurality of reconstructed frames and corresponding plurality of regions of the input frame, and a reconstruction technique used for reconstructing the plurality of reconstructed frames.

Abstract: Example embodiments include a method and an electronic device for detecting and removing artifacts/degradations in media. Embodiments may detect artifacts and/or degradations in the media based on tag information indicating at least one artifact included in the media. The detection may be triggered automatically or manually. Embodiments may generate artifact/quality tag information associated with the media to indicate artifacts and/or degradations present in the media, and may store the artifact/quality tag information as metadata and/or in a database. Embodiments may identify, based on the artifact/quality tag information associated with the media, at least one artificial intelligence (AI)-based media processing model to be applied to the media to enhance the media. The at least one AI-based media processing model may be configured to enhance at least one artifact detected in the media. Embodiments may enhance the media by applying the at least one AI-based media enhancement model to the media.

Abstract: Embodiments herein disclose a method for recommending an image capture mode by an electronic device. The method includes identifying, by the electronic device, at least one ROI displayed in a camera preview of the electronic device for capturing an image in a non-ultra-wide image capture mode. Further, the method includes determining, by the electronic device, that the at least one ROI is suitable to capture in an ultra-wide image capture mode. Further, the method includes providing, by the electronic device, at least one recommendation to switch to the ultra-wide image capture mode from the non-ultra-wide image capture mode for capturing the image.

Abstract: 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.

Abstract: 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.

Abstract: Accordingly the embodiments herein provide a method for rendering a background in an image by an electronic device (100). The method includes recognizing, by the electronic device (100), foreground objects and background objects of the image. Further, the method includes determining, by the electronic device (100), a context of the foreground objects and a context of the background objects in the image. Further, the method includes determining, by the electronic device (100), a background pattern based on the context of the foreground objects and the context of the background objects. Further, the method includes modifying, by the electronic device (100), the background of the image based on the background pattern. Further, the method includes displaying, by the electronic device (100), the image with the modified background.

Abstract: A system and a method for detecting light sources in a multi-illuminated environment using a composite red-green-blue-infrared (RGB-IR) sensor is provided. The method comprises detecting, by the composite RGB-IR sensor, a multi-illuminant area using a visible raw image and a near-infrared (NIR) raw image of a composite RGBIR image, dividing each of the visible raw image and the NIR raw image into a plurality of grid samples, extracting a plurality of illuminant features based on a green/NIR pixel ratio and a blue/NIR pixel ratio, estimating at least one illuminant feature for each grid sample by passing each grid sample through a convolution neural network (CNN) module using the extracted plurality of illuminant features, and smoothing each grid sample based on the estimated at least one illuminant feature.

Abstract: Embodiments herein disclose a method for recommending an image capture mode by an electronic device. The method includes identifying, by the electronic device, at least one ROI displayed in a camera preview of the electronic device for capturing an image in a non-ultra-wide image capture mode. Further, the method includes determining, by the electronic device, that the at least one ROI is suitable to capture in an ultra-wide image capture mode. Further, the method includes providing, by the electronic device, at least one recommendation to switch to the ultra-wide image capture mode from the non-ultra-wide image capture mode for capturing the image.

Abstract: A system and a method for detecting light sources in a multi-illuminated environment using a composite red-green-blue-infrared (RGB-IR) sensor is provided. The method comprises detecting, by the composite RGB-IR sensor, a multi-illuminant area using a visible raw image and a near-infrared (NIR) raw image of a composite RGBIR image, dividing each of the visible raw image and the NIR raw image into a plurality of grid samples, extracting a plurality of illuminant features based on a green/NIR pixel ratio and a blue/NIR pixel ratio, estimating at least one illuminant feature for each grid sample by passing each grid sample through a convolution neural network (CNN) module using the extracted plurality of illuminant features, and smoothing each grid sample based on the estimated at least one illuminant feature.

Abstract: An image processing apparatus and an image processing method are provided. The image processing apparatus includes an image capturer configured to capture a plurality of images having different zoom levels, a storage configured to store the plurality of image, a display configured to display a first image among the plurality of images, and a processor configured to control the display to display a second image among the plurality of images based on a control input, the second image having a zoom level different from a zoom level of the first image.

Abstract: 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.

Abstract: An image processing apparatus and an image processing method are provided. The image processing apparatus includes an image capturer configured to capture a plurality of images having different zoom levels, a storage configured to store the plurality of image, a display configured to display a first image among the plurality of images, and a processor configured to control the display to display a second image among the plurality of images based on a control input, the second image having a zoom level different from a zoom level of the first image.

Abstract: A method and apparatus are provided for enhancing the local dynamic range of an image using the contents of exposure bracketed image set without affecting overall dynamic range of the image. The method allows a user to select at least one region of a reference image for enhancement after receiving the reference image from the user. Further the method comprises segmenting the reference image by using exposure weights, and selects an enhancement support image from an exposure bracketed image set. Furthermore the method determines weight maps of reference and enhancement support images and generates dynamic range enhanced reference image using determined weight maps.

Abstract: 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.

Abstract: A method and an image capturing device configured to generate a defocused image from a reference image and one or more of focal bracketed images to provide an artificially defocused blurred image. The artificially defocused blurred image is a fusion image composed by processing the reference image and one or more of focal bracketed images to provide a clear foreground with gradual blurred background based on a created depth map. The method is time efficient as it provides faster processing on a captured and down sampled reference image and one or more captured down sampled aligned focal bracketed images. The depth map created using region based segmentation reduces a misclassification at a time of classifying foreground-background and misclassification of pixels to provide fast, robust artificial blurring of background in the captured reference image.

Abstract: A method and apparatus are provided for enhancing the local dynamic range of an image using the contents of exposure bracketed image set without affecting overall dynamic range of the image. The method allows a user to select at least one region of a reference image for enhancement after receiving the reference image from the user. Further the method comprises segmenting the reference image by using exposure weights, and selects an enhancement support image from an exposure bracketed image set. Furthermore the method determines weight maps of reference and enhancement support images and generates dynamic range enhanced reference image using determined weight maps.