A low-resolution image is displayed at higher resolution and afterimages are reduced. Resolution is nude higher by super-resolution processing. In this case, the super-resolution processing is performed after frame interpolation processing is performed. Further, in that case, the super-resolution processing is performed using a plurality of processing systems. Therefore, even when frame frequency is made higher, the super-resolution processing can be performed at high speed. Further, since frame rate doubling is performed by the frame interpolation processing, afterimages can be reduced.

Utilizing random variation (repeated positioning error) when reciprocating operation is repeatedly performed in which a stage is moved by (+x, +y) pulses toward an arbitrary position perpendicular to an optical axis of X-rays extending from an X-ray source to an X-ray detector, and then, is moved from there by (−x, −y) pulses, an image group of images obtained by moving in parallel to each other is acquired, and an image processing unit finds a deviation between the images, and acquires an input image group in which each of the images has the deviation at a subpixel level. The image processing unit executes a reconstruction processing, using the input image group in which each of the images has the deviation at the subpixel level to generate a super-resolution image.

An image processing device includes one or more processors configured to: generate a high-resolution combined image by aligning the plurality of images with each other in a high-resolution image space based on an amount of displacement between the plurality of images, and combining the plurality of images; generate at least two low-resolution combined images by generating at least two groups each composed of at least two images by dividing the plurality of images in the time direction, aligning the at least two images in each of the groups with each other in a low-resolution image space based on the amount of displacement, and combining the at least two images through weighted addition; calculate, in each region, a feature quantity pertaining to a correlation between the generated at least two low-resolution combined images; and correct the high-resolution combined image based on the calculated feature quantity.

The present disclosure describes systems and techniques for creating a super-resolution image (122) of a scene captured by a user device (102). Natural handheld motion (110) introduces, across multiple frames (204, 206, 208) of an image of a scene, sub-pixel offsets that enable the use of super-resolution computations (210) to form color planes (212, 214, 216), which are accumulated (218) and combined (220) to create a super-resolution image (122) of the scene.

In one embodiment, a computing system may obtain a high-resolution X-ray image and a number of low-resolution X-ray images of an object of interest. The system may divide each of the low-resolution X-ray images into a number of low-resolution patches. Each low-resolution patch may be associated with a portion of the object of interest. The system may input a set of low-resolution patches associated with a same portion of the object of interest into a machine-learning model. Each low-resolution patch of the set may be from a different low-resolution X-ray image. The machine-learning model may output a high-resolution patch for the same portion of the object of interest. The system may compare the high-resolution patch outputted by the machine-learning model to a corresponding portion of the high-resolution X-ray image of the object of interest and adjust one or more parameters of the machine-learning model based on the comparison.

An image sensor according to an embodiment of the present invention includes: a pixel array in which a plurality of pixels are arrayed in a grid shape, and which converts reflection light signals reflected from an object into electrical signals; an image processor which converts the electrical signals to generate subframes, and extracts pieces of second depth information having a higher resolution than pieces of first depth information extracted from a plurality of the subframes; and a memory for storing the pieces of first depth information, wherein the reflection light signals are input to the pixel array through mutually different optical paths shifted in sub-pixel units of the pixel array, and the memory stores a plurality of the pieces of first depth information that correspond to the mutually different optical paths.

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.

Utilizing random variation (repeated positioning error) when reciprocating operation is repeatedly performed in which a stage is moved by (+x, +y) pulses toward an arbitrary position perpendicular to an optical axis of X-rays extending from an X-ray source to an X-ray detector, and then, is moved from there by (−x, −y) pulses, an image group of images obtained by moving in parallel to each other is acquired, and an image processing unit finds a deviation between the images, and acquires an input image group in which each of the images has the deviation at a subpixel level. The image processing unit executes a reconstruction processing, using the input image group in which each of the images has the deviation at the subpixel level to generate a super-resolution image.

An image display method, a display system, and a computer-readable storage medium are disclosed. The image display method includes: acquiring a first image; determining a first region and a second region in the first image; performing a first rendering algorithm on the first region in the first image and performing a second rendering algorithm on the second region in the first image, so as to obtain a second image, where a rendering resolution of the first rendering algorithm is greater than a rendering resolution of the second rendering algorithm; and displaying the second image.

A low-resolution image is displayed at higher resolution and afterimages are reduced. Resolution is nude higher by super-resolution processing. In this case, the super-resolution processing is performed after frame interpolation processing is performed. Further, in that case, the super-resolution processing is performed using a plurality of processing systems. Therefore, even when frame frequency is made higher, the super-resolution processing can be performed at high speed. Further, since frame rate doubling is performed by the frame interpolation processing, afterimages can be reduced.