[opendtv] Re: Math of oversampling
- From: Craig Birkmaier <craig@xxxxxxxxx>
- To: opendtv@xxxxxxxxxxxxx
- Date: Fri, 29 Apr 2005 05:51:44 -0400
At 9:14 PM -0400 4/28/05, Tom Barry wrote:
>I think we've already once had something of this conversation on
>AVS. I still tend to believe we see images in a blend of two (or
>more) different modes. One would be some sort of edge and/or
>shape perception which is probably not frequency based. But the
>other is our perception of texture, and that one likely does rely
>on frequency. It really seems to me our perception of realistic
>sharpness depends upon both.
It is at times like this that I take a bit of pride in the fact that
the OpenDTV list keeps going, and going, and going. The discussions
of the past few days have been first rate - I hope everyone is
learning as much as I have.
Tom is definitely on the right track with respect to the presence of
specialized receptors in our foveal vision that are tuned to specific
types of stimuli. The following is from the SPTE Task Force Report on
Digital Imaging which I helped author in 1992.
3.2.2 Human Visual Processing
Much of the research in visual science today is focused on the
processing of data acquired by the image receptors. A variety of
specialized analyzers in the eye process data from small localized
regions and accumulate the results into channels which are processed
by the brain to create an integrated view of the physicals
environment.
There is evidence that the brain directs the activity of the image
receptors for processes such as establishing white balance and light
sensitivity levels. Simple localized analyzers are used to enhance
the data transmitted back to the brain. Some of these analyzers are
sensitive to a particular edge orientation; there are sufficient
analyzers at each location to represent a full set of edge
orientations. Additional tuned analyzers cover portions of the range
of human sensitivity for spatial frequency, spatial position,
temporal frequency direction of motion; and binocular disparity.
The data processed by these analyzers moves to the brain through two
types of channels; a set of fast responding channels with relatively
transient responses to stimuli, and a set of slower channels with
relatively sustained responses to stimuli. Transient channels process
the output of analyzers that are tuned for low spatial and high
temporal frequency stimuli. Sustained channels process the output of
analyzers that are tuned for high spatial and low temporal frequency
stimuli.
So yes, we do have a variety of image receptors that are tuned for
the acquisition of various components of an image. One of the
interesting findings of the research that I studied when writing the
report is that we LEARN how to see different edge orientations. There
was a study done with rats where they were raised in an environment
that was devoid of certain edge orientations - I think there were
vertical lines in the environment, but no horizontal lines. When
these rats were later introduced into an environment with edges in
all orientations, they could not see the edges that they had NOT
learned to see; they would run into things because they could not see
them.
It is important to note that there is a huge difference between the
perception of still images and moving images. With still images we
have plenty of time to analyze the image and to perceive fine
details. With moving images the amount of information can overwhelm
the human visual system. We tend to filter out the most important
information and used directed eye movements to acquire high
resolution views of portions of a high resolution image. This is
especially true for
images that cover a large portion of our field of view, such as an
large HDTV display - we cannot sample all of the information in the
image, and are forced to track motion and acquire high resolution
views of a portion of the image while ignoring most of the detail in
other portions of the image. The only problem is that we cannot
predict what a viewer will look at, so we need to have approximately
the same level of detail everywhere.
So while it is interesting to study the images that Tom and Jeroen
have created for us, they only tell us part of the story. It takes
several hundred milliseconds to acquire a high resolution view of any
image, as the foveal receptors dart around to acquire a high
resolution view. Thus in a motion imaging system it is likely that
several temporal samples are contributing to the perception of
sharpness. Detail from several frames can add to improve the
perception of sharpness. One of the early compression systems for
desktop computers simply threw away about 75% of the image samples.
But it did this by moving the sampling points around in a four pixel
region - over a four frame time period all of the sample points in
the original image were presented. This actually worked quite well,
enabling the perception of more image detail than simply down
sampling to a frame 1/4 the size. On the other hand, objects that are
moving need some motion blur - especially at lower frame rates like
24P - in order to fool the human visual system into seeing continuous
motion. So a motion imaging system must deal with many issues as it
attempts to fool the human visual system into seeing sharp, high
resolution moving images.
Regards
Craig
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- » [opendtv] Re: Math of oversampling
- [opendtv] Re: Math of oversampling
- From: John Golitsis
- [opendtv] Re: Math of oversampling
- From: Jeroen Stessen
- [opendtv] Re: Math of oversampling
- From: Don Munsil
- [opendtv] Re: Math of oversampling
- From: Tom Barry