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helpful in removing noise from an image, such as might be introduced by 
electronic defects in the sensor. Figure 1 a shows an aircraft image with 
coherent noise, followed by the final version of the image after removing 
the noise (Fig. 1 b). Low frequency notch filtering can be useful removing 
large scale shading which obscures more interesting local detail. This pro- 
cedure is most frequently implemented in terms of a subtractive box filter, 
in which a local average value is subtracted from each pixel (e.g. Soha 
et al., 1977). Care must be exercised to avoid artifacts (Gillespie, 1976). 
High frequency boost filtering can be used to sharpen edges. Where sensor 
characteristics are known a priori, including noise level, Wiener filtering 
can be employed to quantitatively restore image sharpness with minimum mean 
square error (Helstrom,1967; Arp and Lorre,1976). Figure 2 demonstrates re- 
storation filtering applied to a Mariner 10 view of Earth. 
  
Figure 2: Example of restoration filtering applied to Mariner 10 view 
of the Earth: (a) hefore, (b) after filtering. 
3.2 Geometric Rectification 
Imagery is mostly acquired with a geometry that needs correction for 
efficient image analysis. The main purpose of rectification is to relate the 
image to other data, be they in the form of maps, of other images or of 
non-images such as terrain relief etc. Anuta (1977) differentiates between 
(a) the "open-loop" rectification employing merely information on predictable 
geometric errors derived from the imaging process, Sensor attitude and posi- 
tion (compare Fig. 1c); and(b) the "fine correction" using ground control 
points. Photogrammetrists have been working in this field for many years 
(see ISP - Working Group III/1 on "Metric Aspects of Remote Sensing", 
operating since 1972). 
It is well established that presently available digital satellite images 
(Landsat, Nimbus) can be rectified with remaining errors of less than one 
pixel and limits set by the geometric resolution (Figure 3). For aircraft 
Scanner images, the rectification &ccuracy has been found to be several pixels 
(Baker et al., 1975). The limits of accuracy seem to be set by the random 
errors of sensor motion &nd imaging, not by geometric resolution. The 
accuracy numbers for both the satellite and the aircraft strongly depend 
on the density of ground control. Experiences on the interrelation of image 
resolution, type of imagery and control point density are however not ex- 
tensive. 
Geometric rectification may result merely in a mathematical expression 
for the deformations, or it may in addition produce a rectfied image.