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Computer vision syndrome (CVS) is a condition resulting from focusing the eyes on a computer or other display device for protracted, uninterrupted periods of time and the eye's muscles being unable to recover from the constant tension required to maintain focus on a close object.
Statistically, images have more low-frequency than high-frequency content, so it is the low-frequency content that remains after quantization, which results in blurry, low-resolution blocks. In the most extreme case only the DC-coefficient, that is the coefficient which represents the average color of a block, is retained, and the transform ...
Visual snow is a phenomenon where a person perceives visual disturbances, such as fine graininess or "static," in their field of vision. This can occur in low-light conditions, in the dark, or when the visual system amplifies light perception.
Saccadic masking, also known as (visual) saccadic suppression, is the phenomenon in visual perception where the brain selectively blocks visual processing during eye movements in such a way that neither the motion of the eye (and subsequent motion blur of the image) nor the gap in visual perception is noticeable to the viewer.
java.nio (NIO stands for New Input/Output [1] [2]) is a collection of Java programming language APIs that offer features for intensive I/O operations. It was introduced with the J2SE 1.4 release of Java by Sun Microsystems to complement an existing standard I/O. NIO was developed under the Java Community Process as JSR 51. [3]
In order to see a clear image, the eye must focus rays of light on to the light-sensing part of the eye – the retina, which is located in the back of the eye.This focusing – called refraction – is performed mainly by the cornea and the lens, which are located at the front of the eye, the anterior segment.
A vision transformer (ViT) is a transformer designed for computer vision. [1] A ViT decomposes an input image into a series of patches (rather than text into tokens ), serializes each patch into a vector, and maps it to a smaller dimension with a single matrix multiplication .
Image restoration: Image restoration focuses on solving the problem = + where is the blurry image that should be restored, is the blur kernel, is the additive noise and is the original image we wish to recover. The traditional filter which is used to solve this problem is the Wiener Filter.