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An Examination Of NASA's
Color Methods
Some consistent errors are
responsible for the incorrect colors in NASA images
Note: the filter errors
referred to have since been corrected by NASA
Some rather
interesting and uncorrected errors are responsible for the poor quality of the
color images that we have recently seen released by NASA. There are three
errors in particular that contribute to the overall problem. The first is
that in some images, the filter values have been incorrectly listed. The
second is that the left and right camera filter values have been swapped in some
images. The third is simply that the wrong filters have been selected to
assemble some of the images.
Taken together,
these explain exactly why some images are odd or misbalanced in color, and
others are outright wrong. I will show how the calibration targets ended
up with wrong colors and how to correct them, and also how to explain in greater
detail why the Martian sky ends up being the wrong color.
The first error
is in assigning filter frequencies. I have selected three frames of data
for assembly into a full color image. To get right to the root of the
problem, I will use data from Opportunity, Sol 001. This is where some of
the errors are most easily seen and verified by anyone.
| This image is from the
left panoramic camera using filter L2. The filter is being used as
the red data for the color picture. The caption on the image is as
follows:
Left Panoramic Camera Non-linearized Full frame EDR acquired on Sol 1
of Opportunity's mission to Meridiani Planum at approximately 16:02:12
Mars local solar time, camera commanded to use Filter 2 (19 nm).
NASA/JPL/Cornell
In other words, this image used a
filter at a wavelength of 19 nm. But this is clearly
impossible. 19 nm would be gamma rays!
In fact, the true wavelength of this
filter is stated as 753 nm by NASA. What is posted is the
"width" of the filter- the pass bandwidth.
This sort of error would not be
noticed by anyone other than somebody familiar with optics or
physics. But the image assembly team surely is aware of this error.
As a side note, the wavelength of 753
nm is not red light- instead it is infrared. Human eyes are barely
sensitive to this wavelength and it contributes no effective light to a
normal color picture.
To see the original caption on the
NASA site, click the image or click
here. |
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| This image is from the L5
filter. This filter is stated as being at a wavelength of 535
nm. However, the caption on the NASA site is thus:
Left Panoramic Camera Non-linearized Downsampled EDR acquired on Sol 1
of Opportunity's mission to Meridiani Planum at approximately 16:02:45
Mars local solar time, camera commanded to use Filter 5 (25 nm).
NASA/JPL/Cornell
In other words, this is supposed to
be at a wavelength of 25 nm, but once again, this would be very energetic
gamma radiation, not visible. light.
This sort of "light" would
spontaneously render matter radioactive.
This frame represents green light
present in the scene that the rover camera was imaging.
To see the original caption on the
NASA site, click the image or click
here.
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| Finally we come to the
blue frame. This is using filter L6 and is at a wavelength of 483
nm. This is a good blue for most purposes and is fine for the color
imaging process. The NASA caption reads:
Left Panoramic Camera Non-linearized Downsampled EDR acquired on Sol 1
of Opportunity's mission to Meridiani Planum at approximately 16:03:16
Mars local solar time, camera commanded to use Filter 6 (24 nm).
NASA/JPL/Cornell
And indeed, we see the same mistake
has been made. The passband of 24 nm has been listed, but that tells
us nothing of the color. It only tells us how wide the spectrum is
that the filter will admit.
What we really need to know is that
filter L6 passes lightwaves with a length of 483 nm, and allows waves of
that frequency, plus or minus 12 nm. So light from 495 nm to 471 nm
is let into the camera when you use this filter.
To see the original caption on the
NASA site, click the image or click
here.
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If we use these raw "monochrome"
images, we can recreate the color of each and then make a full color image from
that data. Here is how.
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