A medical system including a medical imaging device, and circuitry that obtains a plurality of first images each having a different phase from the medical imaging device, combines each of the plurality of first images a plurality of times to generate a plurality of second images, wherein each time of the plurality of times that the plurality of first images are combined, a different candidate process is used in the combining, and selects one image from the plurality of second images as an output image for display, the selected one image being higher quality than any one of the plurality of first images.

Provided is a super-resolution image sensor and a producing method thereof such that, on the basis of not changing the arrangement of the image sensitive unit array of the image sensor, by means of the existing micro-lens manufacture techniques, the imaging resolution can be increased by offsetting micro-lens rows in a micro-lens array that covers upon the image sensitive unit array. In some examples, a super-resolution image sensor comprises an image sensitive unit array having image sensitive unit rows aligned with one another, and a micro-lens array covering upon the image sensitive unit array. Relative to a reference micro-lens row in the micro-lens array, the other micro-lens rows are regularly offset. Each micro-lens unit in the reference micro-lens row is center aligned with a corresponding image sensitive unit in a reference image sensitive unit row.

This invention describes a technique to enhance pixel resolution of high-speed laser scanning imaging by the means of sub-pixel sampling, applicable to one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) imaging.

A processing device is provided which includes memory and a processor. The processor is configured to receive an input image having a first resolution, generate linear down-sampled versions of the input image by down-sampling the input image via a linear upscaling network and generate non-linear down-sampled versions of the input image by down-sampling the input image via a non-linear upscaling network. The processor is also configured to convert the down-sampled versions of the input image into pixels of an output image having a second resolution higher than the first resolution and provide the output image for display

In a method for super resolution imaging, the method includes: receiving, by a processor, a low resolution image; generating, by the processor, an intermediate high resolution image having an improved resolution compared to the low resolution image; generating, by the processor, a final high resolution image based on the intermediate high resolution image and the low resolution image; and transmitting, by the processor, the final high resolution image to a display device for display thereby.

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.

Methods, devices and non-transitory computer-readable storage medium for processing a sequence of respective top view images of a same terrestrial location are provided. One of the method may comprise choosing one image, called reference image, among the respective top view images, estimating for each respective top view image a respective geometric deformation between the respective top view image and the reference image, computing by the respective geometric deformations respective subpixel positions of the respective top view images relative to one high-resolution coordinate system, interpolating at the respective subpixel positions to sample at least part of at least some of the respective top view images on a prescribed grid to obtain a high-resolution image.

The technology disclosed relates to structured illumination microscopy (SIM). In particular, the technology disclosed relates to capturing and processing, in real time, numerous image tiles across a large image plane, dividing them into subtiles, efficiently processing the subtiles, and producing enhanced resolution images from the subtiles. The enhanced resolution images can be combined into enhanced images and can be used in subsequent analysis steps.

The technology disclosed relates to structured illumination microscopy (SIM). In particular, the technology disclosed relates to capturing and processing, in real time, numerous image tiles across a large image plane, dividing them into subtiles, efficiently processing the subtiles, and producing enhanced resolution images from the subtiles. The enhanced resolution images can be combined into enhanced images and can be used in subsequent analysis steps. The technology disclosed includes logic to reduce computing resources required to produce an enhanced resolution image from structured illumination of a target. A method is described for producing an enhanced resolution image from images of a target captured under structured illumination. This method applies one or more transformations to non-redundant data and then recovers redundant data from the non-redundant data after the transformations.

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.