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Foveated imaging is a digital image processing technique in which the image resolution, or amount of detail, varies across the image according to one or more "fixation points." A fixation point indicates the highest resolution region of the image and corresponds to the center of the eye's retina, the fovea.
The location of a fixation point may be specified in many ways. For example, when viewing an image on a computer monitor, one may specify a fixation using a pointing device, like a computer mouse. Eye trackers which precisely measure the eye's position and movement are also commonly used to determine fixation points in perception experiments. When the display is manipulated with the use of an eye tracker, this is known as a gaze contingent display. Fixations may also be determined automatically using computer algorithms.
Foveated imaging is also commonly referred to as space variant imaging or gaze contingent imaging.
Contrast sensitivity falls off dramatically as one moves from the center of the retina to the periphery. One may take advantage of this fact in order to compactly code images. If one knows the viewer's approximate point of gaze, one may reduce the amount of information contained in the image as the distance from the point of gaze increases. Because the fall-off in the eye's resolution is dramatic, the potential reduction in display information can be substantial. Also, foveation encoding may be applied to the image before other types of image compression are applied and therefore can result in a multiplicative reduction.
Foveated sensors are multiresolution hardware devices that allow image data to be collected with higher resolution concentrated at a fixation point. An advantage to using foveated sensor hardware is that the image collection and encoding can occur much faster than in a system that post-processes a high resolution image in software.
Foveated imaging has been used to simulate visual fields with arbitrary spatial resolution. For example, one may present video containing a blurred region representing a scotoma. By utilizing an eye-tracker and holding the blurred region fixed relative to the viewer's gaze, the viewer will have a visual experience similar to that of a person with an actual scotoma. The figure on the right shows a frame from a simulation of a glaucoma patient with the eye fixated on the word "similar."
Foveated imaging may be useful in providing a subjective image quality measure. Traditional image quality measures, such as peak signal-to-noise ratio, are typically performed on fixed resolution images and do not take into account some aspects of the human visual system, like the change in spatial resolution across the retina. A foveated quality index may therefore more accurately determine image quality as perceived by humans.
Image database retrieval
In databases that contain very high resolution images, such as a satellite image database, it may be desirable to interactively retrieve images in order to reduce retrieval time. Foveated imaging allows one to scan low resolution images and retrieve only high resolution portions as they are needed. This is sometimes called progressive transmission.
Image with foveated luminance channel
Foveated image with fixation selected using an entropy minimization algorithm
Foveated image with fixation on bee in upper-left flower
Same foveated image with fixation on butterfly in center
18:1 compression. Foveated image with fixation point on tombstone.
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