Image Resolution
Chapter 10
Definitions
• Resolution – ability to record and
display detail
• Spatial
• Spectral
• Radiometric
Definitions
• Spatial resolution – the amount of
geometric detail
• How close can two points be before you
can’t distinguish them
Spatial Resolution
• High spatial resolution: 0.6 - 4 m
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» GeoEye-1
» WorldView-2
» WorldView-1
» QuickBird
» IKONOS
» FORMOSAT-2
» ALOS
» CARTOSAT-1
» SPOT-5
• Medium spatial resolution: 4 - 30 m
• » ASTER
• » LANDSAT 7
• » CBERS-2
• Low spatial resolution: 30 - > 1000 m
• SeaWiFS
• GOES
Radiometric Resolution
• Radiometric resolution – the amount
of brightness detail
• Is the image black and white, shades of
grey
• How many bits – 4, 8, 12, 16, etc.
Radiometric Resolution
8 bit
6 bit
2 bit
1 bit
2-bit
8-bit
Spectral Resolution
• Spectral resolution – the amount of
detail in wavelength
• 2 bands, 4, 6, 200 or more
Temporal Resolution
• Temporal resolution – the amount of
detail in time
• High altitude aerial photos every 10
years, Landsat 16 days, NOAA 4 hrs
• High resolution: < 24 hours - 3 days
• Medium resolution: 4 - 16 days
• Low resolution: > 16 days
Tradeoffs
Tradeoffs
• There are trade-offs between spatial,
spectral, and radiometric resolution
• Taken into consideration when engineers
design a sensor.
• For high spatial resolution, the sensor has
to have a small IFOV (Instantaneous Field
of View).
• However, this reduces the amount of
energy that can be detected as the area of
the ground resolution cell within the IFOV
becomes smaller.
• This leads to reduced radiometric
resolution - the ability to detect fine
energy differences.
Tradeoffs
• To increase the amount of energy
detected (and the radiometric resolution)
without reducing spatial resolution, we
have to broaden the wavelength range
detected for a particular channel or band.
• Unfortunately, this reduces the spectral
resolution of the sensor.
• Conversely, coarser spatial resolution would
allow improved radiometric and/or spectral
resolution.
• Thus, these three types of resolution must
be balanced against the desired
capabilities and objectives of the sensor.
Target Variables
• Contrast – the brightness difference
between an object and the
background
• High contrast improves spatial detail
Contrast versus spatial frequency
Sinusoidal target with
varying contrast in %
and varying spatial
frequency left to right
Obvious resolution
decrease from left to
right. If your eyes are too
good squint to see effect
Picture from
www.normankoren.com/
Tutorials/MTF.html
Target Variables
• Shape is also a significant factor
• Aspect ratio is how long the object is
compared to its width
• Long thin features can be seen even if
they are narrower than the spatial
resolution
• Regularity of shape makes for better
detail
• Agricultural fields
Target Variables
• Number of objects favor higher detail
• Orchard versus single tree
• Extent and uniformity of background
also helps distinguish things
Aerial view of Olympic Peninsula facing west from Port Orchard Bay
System Variables
• Design of sensor and its operation
are important too
• Air photo – have to consider quality of
camera and lens, choice of film, altitude,
scale,
Operating conditions
• Altitude
• Ground speed
• Atmospheric conditions
Measuring resolution
• Ground Resolved Distance (GRD) the
dimensions of the smallest objects
recorded
• Line pairs per millimeter (LPM) is
derived from targets
• Target is placed on the ground and
imaged
• If two obejcts are are visually
separated, they are considered
“spatially resolved”
Measuring resolution
• Using the target you measure the
smallest pair of lines (black line plus
adjacent white space)
Modulation Transfer Function
• The Modulation Transfer Function
(MTF) is response of a system to an
array of elements with varying
spaces
Modulation Transfer Function
• For low spatial frequencies, the
modulation transfer function is close to 1
(or 100%)
• generally falls as the spatial frequency
increases until it reaches zero.
• The contrast values are lower for higher
spatial frequencies .
• As spatial frequency increases, the MTF
curve falls until it reaches zero.
• This is the limit of resolution for a given optical
system or the so called cut off frequency (see
figure below).
• When the contrast value reaches zero, the
image becomes a uniform shade of grey.
Modulation Transfer Function
Modulation Transfer Function
• The figure represents a sine pattern
(pure frequencies) with spatial
frequencies from 2 to 200 cycles (line
pairs) per mm.
• The top half of the sine pattern has
uniform contrast.
Modulation Transfer Function
• Perceived image sharpness (NOT
lp/mm resolution) is closely related
to the spatial frequency where MTF is
50% (0.5)
• i.e. where contrast has dropped by half.
Modulation Transfer Function
• Contrast levels from 100% to 2% are
illustrated on the chart for a variable
frequency sine pattern.
• Contrast is moderately attenuated for MTF
= 50% and severely attenuated for MTF =
10%.
• The 2% pattern is visible only because
viewing conditions are favorable:
• it is surrounded by neutral gray, it is noiseless
(grainless), and the display contrast for CRTs
and most LCD displays is relatively high.
• It could easily become invisible under less
favorable conditions.
Modulation Transfer Function
• How is MTF related to lines per
millimeter resolution?
• The old resolution measurement—
distinguishable lp/mm— corresponds
roughly to spatial frequencies where
MTF is between 5% and 2% (0.05 to
0.02).
• This number varies with the observer,
most of whom stretch it as far as they
can.
• An MTF of 9% is implied in the definition of
the Rayleigh diffraction limit.
Mixed Pixels
• If the area covered by a pixel is not
uniform in composition it leads to
mixed pixels.
• These often occur at the edge of
large parcels, along linear features,
or scattered due to small features in
the landscape (ponds, buildings,
vehicles, etc.)
Mixed Pixels
Mixed Pixels
• The spectral responses of those
mixed pixels is not a pure signature,
but rather, a composite signature
• Can you think of an advantage to
having a composite signature?
• Identify areas that are too complex to
resolve individually
• There have been a number of studies
on the effect of resolution on mixed
pixels
• As resolution becomes coarser
• Mixed pixels increase
• Interior pixels decrease
• Background pixels decrease
Resolution and Mixed Pixels
Resolution Total
Mixed
Interior
Background
A - fine
900
%
109
1.1
143
15.9
648
72
B
225
%
59
26.2
25
11.1
141
62.7
C
100
%
34
34
6
6
60
60
23
46.9
1
2
25
51
D - coarse 49
%
Original Landsat image
Image resampled at coarser resolution
wheat (red), potatoes (green) and sugar beet (blue)
Spatial and Radiometric Resolution
• Sensors are designed with specific
levels of radiometric resolution and
spatial resolution
• Both of these determine the ability to
portray features in the landscape
• Broad levels of resolution may be
adequate for coarse-textured
landscape
• Finer resolution may help to identify
more features, but may also add
more detail than necessary
Interactions with Landscape
• In a study of field size in grainproducing regions, Podwysocki
(1976) showed how effectiveness of
different resolutions could be
quantified.
Interactions with Landscape
• Simonett and Coiner (1971)
conducted another study to
determine the effectiveness of the
yet to be launched MSS sensor
• Simulated by using airphotos and
overlaying a grid of 800, 400, 200,
and 100 feet.
• Assessed the number of land-use
categories in each cell