The technology disclosed present systems and methods to produce an enhanced resolution image from images of a target using structured illumination microscopy (SIM). The method includes transforming at least three images of the target captured by a sensor in a spatial domain into a Fourier domain to produce at least three frequency domain matrices that each include first blocks of complex coefficients and redundant second blocks of complex coefficients that are conjugates to the first blocks. The method includes reducing computing resources required to produce the enhanced resolution image by using first blocks of complex coefficients to produce at least three phase-separated half-matrices in the Fourier domain. The method includes performing one or more intermediate transformation on the phase-separated half-matrices to produce realigned shifted half-matrices. The method includes calculating complex coefficients of second blocks in the Fourier domain to produce full matrices from half-matrices.

An electronic device that outputs at least one calibration point through a display, obtains gaze information corresponding to the at least one calibration point by using a gaze tracking sensor in response to an output of guide information instructing a user wearing the electronic device to gaze at the at least one calibration point, obtains a gaze accuracy corresponding to the at least one calibration point based on the obtained gaze information, determines a gaze zone-specific resolution based on the gaze accuracy corresponding to the at least one calibration point, and outputs an image through the display based on the determined gaze zone-specific resolution.

Apparatuses, systems, and techniques are presented to generate images. In at least one embodiment, one or more neural networks are used to generate one or more images using one or more pixel weights determined based, at least in part, on one or more sub-pixel offset values.

Embodiments relate to generating keypoint descriptors of the keypoints using a sub-scale refinement and a sample pattern radius adjustment. An apparatus includes a sub-pixel refiner circuit and a keypoint descriptor generator circuit. The sub-pixel refiner circuit determines a keypoint scale value for a scale dimension of a keypoint in an image pyramid by performing an interpolation of response map (RM) pixel values of a pixel block of RM images defined around the keypoint. The keypoint descriptor generator circuit determines sample scales of the image pyramid based on the keypoint scale value and determines a radius value for each sample scale based on the keypoint scale value. The keypoint descriptor generator circuit samples patches of pixel values at the sample scales using the radius value for each sample scale to generate a keypoint descriptor of the keypoint.

An image processing method includes a matching cost calculating process of calculating matching costs in a unit of sub-pixels having higher resolution than first and second images by using an image of a reference area contained in the first image in which a target object is imaged and images of a plurality of comparison areas contained in the second image in which the target object is imaged, and a synthesized cost calculating process of calculating synthesized costs related to the reference area based on comparison results of values related to the plurality of matching costs calculated in the matching cost calculating process.

A method is provided for enhancing video images in a medical device. The method includes receiving a first image frame and a second image frame from one or more image sensors. The first image sub-blocks are generated by dividing the first image frame. At least one curve to the first image sub-blocks are associated based on one or more look-up tables. A target in at least one of the first image sub-blocks is identified. Second image sub-blocks are generated by dividing the second image frame. At least one curve is associated to the second image sub-blocks based on the one or more look-up tables. The target is identified in at least one of the second image sub-blocks. Histogram enhanced images of the target in the first image sub-blocks and the second image sub-blocks are generated. A video image stream is generated based on the histogram enhanced images of the target.

Apparatuses, systems, and techniques are presented to generate images. In at least one embodiment, one or more neural networks are used to generate one or more images using one or more pixel weights determined based, at least in part, on one or more sub-pixel offset values.

Apparatuses, systems, and techniques are presented to generate images. In at least one embodiment, one or more neural networks are used to generate one or more images using one or more pixel weights determined based, at least in part, on one or more sub-pixel offset values.

Apparatuses, systems, and techniques are presented to generate images. In at least one embodiment, one or more neural networks are used to generate one or more images using one or more pixel weights.

A camera system captures an image in a source aspect ratio and applies a transformation to the input image to scale and warp the input image to generate an output image having a target aspect ratio different than the source aspect ratio. The output image has the same field of view as the input image, maintains image resolution, and limits distortion to levels that do not substantially affect the viewing experience. In one embodiment, the output image is non-linearly warped relative to the input image such that a distortion in the output image relative to the input image is greater in a corner region of the output image than a center region of the output image.