An inspection tool comprises an imaging system configured to image a portion of a semiconductor substrate. The inspection tool may further comprise an image analysis system configured to obtain an image of a structure on the semiconductor substrate from the imaging system, encode the image of the structure into a latent space thereby forming a first encoding. the image analysis system may subtract an artifact vector, representative of an artifact in the image, from the encoding thereby forming a second encoding; and decode the second encoding to obtain a decoded image.

Image processing includes obtaining image I[0,0] of a picture captured by an image capture means, in a state where light is irradiated to the picture from a light source at a reference position relative to a normal line of the picture, obtaining image I[α1,0] of the picture captured by an image capture means, in a state where the light is irradiated to the picture from the light source at a position inclined from the reference position at an angle α1 in the first direction, obtaining image I[0, β1] of the picture captured by an image capture means, in a state where the light is irradiated to the picture from the light source at a position inclined by an angle β1 from the reference position in a second direction different from the first direction, creating a three-dimensional map of the picture, using a set of images I[0, β1] and I[0, β2], merging at least a part of each of image I[α1,0], image I[0,β1], and image I[0,β2] with respect to image I[0,0], and recording as two-dimensional image data the image subjected to the emphasizing process.

A control apparatus includes a control unit that adjusts at least one of a color and luminance of a projection image for each group of the plurality of projection apparatuses based on information on the group and a captured image obtained by imaging projection images of the plurality of projection apparatuses using the pickup apparatus. The control unit acquires each of positions of a plurality of projection areas of the plurality of projection apparatuses based on the captured image, and generates, as the information on the group, information indicating that two projection apparatuses corresponding to a first projection area and a second projection area belong to the same group in a case where a distance between the first projection area and the second projection area among the plurality of projection areas is smaller than a predetermined threshold.

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.

A digital graduated filter is implemented in an imaging device by combining multiple images of the subject wherein the combining may include combining different numbers of images for highlights and for shadows of the subject. The imaging device may present a user with a set of pre-defined graduated filter configurations to choose from. A user may also specify the direction of graduation and strength of graduation in a viewfinder. In an alternative implementation, combining may include scaling of pixels being added instead of varying the number of images being combined. In an alternative implementation, the combining of multiple images may include combining a different number of images for highlights of the subject than for shadows of subject.

An image processing method includes: determining a first face mask image that does not contain hair from a target image, and obtaining a first face region that does not contain hair from the target image according to the first face mask image; filling a preset grayscale color outside the first face region to generate an image to be sampled; performing down-sampling on the image to be sampled to obtain sampling results, and obtaining remaining sampling results by removing one or more sampling results in which a color is the preset grayscale color from the sampling results; obtaining a target color by calculating a mean color value of the remaining sampling results and performing weighted summation on a preset standard face color and the mean color value; rendering pixels in a face region of the target image according to the target color.

A method of adjusting brightness of a foreground video displayed over a background in a user device is provided. The method includes determining enhancement factors for background sections in a background frame of the background, determining an enhancement mask for each foreground sub-frame of the foreground video based on enhancement factor of corresponding background section and determining enhanced brightness values for each foreground pixel in the foreground video based on the enhancement mask. The method of the disclosure provides real-time, clear and distinct viewing of an enhanced foreground video in varying brightness conditions of the background sections.

Disclosed is an image processing method employing a post processing technique that may eliminate flicker artifacts from captured video in real time. An example method involves receiving from an image sensor a sequence of input frames representing a scene and identifying and tracking a light source represented within the input frames. Flickering of the light source may be identified by detecting frame to frame color characteristic variation of a region representing the light source. A sequence of output frames may be generated with the flickering removed by selectively modifying image data of pixels within the region.

The disclosure provides an image processing device. An image processing device includes a neural network circuit, a gain control circuit, and an image merge circuit. The neural network circuit is configured to receive an input image, and perform an image processing operation on the input image according to fixed parameters to output a first intermediate image. The gain control circuit, coupled to the neural network circuit, is configured to receive the first intermediate image from the neural network circuit, and multiply the first intermediate image by at least one amplitude gain to output a second intermediate image. The image merge circuit, coupled to the gain control circuit, configured to receive the second intermediate image and the input image, and combine the second intermediate image and the input image to obtain an output image. In addition, a method for image enhancement is also provided.

A method of generating a high dynamic range (HDR) image is provided that includes capturing a long exposure image and a short exposure image of a scene, computing a merging weight for each pixel location of the long exposure image based on a pixel value of the pixel location and a saturation threshold, and computing a pixel value for each pixel location of the HDR image as a weighted sum of corresponding pixel values in the long exposure image and the short exposure image, wherein a weight applied to a pixel value of the pixel location of the short exposure image and a weight applied to a pixel value of the pixel location in the pixel long exposure image are determined based on the merging weight computed for the pixel location and responsive to motion in a scene of the long exposure image and the short exposure image.