Abstract:
An optimization method includes determining first information related to a difference between the color filter spectrum and the color spectrum or a difference between an image transformed by the color transformation matrix and a ground truth (GT) image in the reset color space, determining second information representing smoothness of the color filter spectrum, third information representing a transmittance of the color filter spectrum, calculating a cost value based on the first information, the second information, and the third information, compare the calculated cost value and a threshold, and updating one of the filter spectrum information and the color transformation matrix in response to the calculated cost value being equal to or greater than the threshold.
Abstract:
An electronic device includes an image sensor including a color filter having a plurality of color channels, a memory storing a plurality of color conversion matrices and instructions, and a processor. The processor is configured to obtain noise information of a color image captured by the image sensor, select a target matrix from among the plurality of the color conversion matrices based on the obtained noise information, and generate a color converted image by applying the selected target matrix to the color image.
Abstract:
An optimization method includes determining first information related to a difference between the color filter spectrum and the color spectrum or a difference between an image transformed by the color transformation matrix and a ground truth (GT) image in the reset color space, determining second information representing smoothness of the color filter spectrum, third information representing a transmittance of the color filter spectrum, calculating a cost value based on the first information, the second information, and the third information, compare the calculated cost value and a threshold, and updating one of the filter spectrum information and the color transformation matrix in response to the calculated cost value being equal to or greater than the threshold.
Abstract:
A target tracking method and apparatus is provided. The target tracking apparatus includes a memory configured to store a neural network, and a processor configured to extract feature information of each of a target included in a target region in a first input image, a background included in the target region, and a searching region in a second input image, using the neural network, obtain similarity information of the target and the searching region and similarity information of the background and the searching region based on the extracted feature information, obtain a score matrix including activated feature values based on the obtained similarity information, and estimate a position of the target in the searching region from the score matrix.
Abstract:
Disclosed is a color transform method performed by an electronic device that includes generating an initial color transformed image by performing color transform on a raw image, determine noise amplification degrees indicating degrees to which noise included in the raw image is amplified by the color transform, processing the determined noise amplification degrees, and generating a final color transformed image by filtering the generated initial color transformed image using the processed noise amplification degrees and at least one of the raw image or luminance information of the raw image.
Abstract:
A target tracking method and apparatus is provided. The target tracking apparatus includes a memory configured to store a neural network, and a processor configured to extract feature information of each of a target included in a target region in a first input image, a background included in the target region, and a searching region in a second input image, using the neural network, obtain similarity information of the target and the searching region and similarity information of the background and the searching region based on the extracted feature information, obtain a score matrix including activated feature values based on the obtained similarity information, and estimate a position of the target in the searching region from the score matrix.
Abstract:
A method and apparatus for color space conversion are provided. An apparatus for converting a color space includes at least one processor configured to convert an original full image of an original color space to a temporary image of a target color space, estimate a color space mapping parameter between the original color space and the target color space, the color space mapping parameter corresponding to the original full image, obtain a residual vector of the target color space based on the temporary image and the color space mapping parameter, convert the residual vector to a residual image of the target color space, and obtain a target full image of the target color space by combining the residual image with the temporary image.
Abstract:
A target tracking method and apparatus is provided. The target tracking apparatus includes a memory configured to store a neural network, and a processor configured to extract feature information of each of a target included in a target region in a first input image, a background included in the target region, and a searching region in a second input image, using the neural network, obtain similarity information of the target and the searching region and similarity information of the background and the searching region based on the extracted feature information, obtain a score matrix including activated feature values based on the obtained similarity information, and estimate a position of the target in the searching region from the score matrix.
Abstract:
Disclosed are target tracking methods and apparatuses. The target tracking apparatus performs target tracking on an input image obtained in a first time period within a single time frame, using a light neural network in a second time period of the single time frame. The target tracking apparatus may perform target tracking on input images generated within the same time frame.
Abstract:
An image processing method includes adjusting a brightness of each of a first image and a second image based on a first exposure time when the first image is captured and a second exposure time when the second image is captured, respectively, the first and second images being generated by capturing a same object under different light conditions, estimating an intensity of light, reaching the object when the second image is captured, based on the adjusted brightness of each of the first and second images, separating the second image into two or more regions according to the estimated intensity of light, determining a target brightness that a final result image is to have, adjusting the brightness of the second image, by different amounts for each of the separated regions, based on the target brightness and generate the final result image based on the adjusted brightness of the second image.