Samsung Electronics Co., Ltd.

Yonsei University

Moon Gi Kang

Min Sub Kim

Keechang Lee

Min Kyu Park

Seunghoon Jee

Seung Hoon Jee

Minsub Kim

Sang Yoon Lee

Sangyoon Lee

Sunghoon Hong

Wooshik Kim

Hwiryong Jung

Sung Dae Cho

Hyun Hee Park

Inhwan Ryu

Jin I Song

Hyewon Moon

Jong Seong Choi

Soonyoung Hong

Young Seok Han

Soon Young Hong

A method and apparatus with image processing are disclosed. The method includes determining a real part image, an imaginary part image, and an offset image based on input images that are dependent on infrared rays of different phases, removing noise from each of the real part image and the imaginary part image using the offset image as a noise removal guide, and generating a depth image based on an improved real part image and an improved imaginary part image corresponding to respective results of the removing.

Method and apparatus with image processing

An image processing method includes: determining a source transmission map based on a dark channel map of an input image; determining transformed transmission maps by applying different filters to the determined source transmission map; generating haze-free images by removing haze from the input image based respectively on the determined transformed transmission maps; and generating an output image by blending the generated haze-free images.

An image processing method acquires an image, restores a saturated region in which a pixel in the image has a first reference value based on a first illuminance component of the image, enhances a dark region in which a value of a pixel in the image is less than a second reference value based on the restored saturated region and the first illuminance component, and outputs a dark region-enhanced image.

Image processing method and apparatus

An image recovery apparatus and method are provided, where the image recovery apparatus calculates a reference color image based on a linear correlation between a color channel image and a luminance channel image, and corrects the luminance channel image based on residual information that indicates a difference between the reference color image and the color channel image, to recover an image.

Method and apparatus for recovering image

A dynamic range enhancement method and apparatus for an imaging device expands a dynamic range of an input image without an associated increase in the amount of image calculations. The dynamic range enhancement method includes producing brightness information and color information from an input image; applying gamma correction and inverse gamma correction to the brightness information to produce a gamma corrected image and an inverse gamma corrected image; comparing variances of the gamma corrected image and the inverse gamma corrected image at identical spots; and expanding a dynamic range of the input image by selecting one of the variances at each spot. The dynamic range of an input image is expanded by applying a post imaging process without increasing calculation amount of the imaging device.

Dynamic range enhancement method and apparatus

There is provided a de-interlacing method including: receiving first and third image lines; selecting an upper vector having an N number of pixels among the first image lines, and selecting a lower vector having an N number of pixels among the third image lines; obtaining a weighted value on the basis of a relation between the pixels within the upper vector and a relation between the pixels within the lower vector; selecting an edge direction from the selected upper vector, the selected lower vector, and the obtained weighted value; and interpolating a pixel belonging to a second image line between the first and third image lines on the basis of the selected edge direction.

De-interlacing algorithm responsive to edge pattern

A numerical control method includes the steps of (a) reading an instruction block from a numerical control program; (b) if a predetermined mirror image code is in the instruction block, determining the coordinates of a target location according to the code; (c) adding predetermined interpolation data to the target location coordinates; and (d) moving a tool to the target location to produce the same cutting direction as an original cutting. Thus, uniform machining precision can always be obtained.

Numerical controlling method with mirror image function

A tool travel path creating method for a numerical control device comprises the steps of reading G-code program; determining whether or not any correction command is included in the read G-code program; determining whether or not the interior angle between a first vector, being a line segment from a start point of correction to a work starting point, and a second vector, being a line segment from the work starting point to an work ending point, is acute when a correction command is included in the read G-code program, and then creating a tool travel path to be corrected in accordance with the following steps: calculating and storing data for a third vector starting from the work starting point and with a direction perpendicular to the first vector and the same length as the radius of the tool; calculating and storing data for a fourth vector starting from the work starting point and formed by adding the second vector to an intermediary vector with the same direction as the second vector and the same length as the radius of the tool; a fifth vector starting from the work starting point and with a direction perpendicular to the second vector and the same length as the radius of the tool; and, calculating and storing data for a sixth vector starting from the work starting point and with the same direction as the first vector and a length of 2.sup.1/2 times the radius of the tool.

Growing community of inventors

Seoul, South Korea

Moon Gi Kang