- data format manipulations; - radiometric restoration; - geometric
rectification; - image enhancement; - image compression (decompression);
- p&ttern recognition; - image annotation.
Data format manipulations, compression and image annotation. will not
be discussed here. They are important topics and deserve thorough considera-
tion in an image processing system, but are of limited relevance in the pre-
sent context.
3.1 Radiometric Restoration
Andrews and Hunt (1977) define image restoration as the techniques to
remove degrading phenomena from images. Image degradations are numerous
and familar to photo-interpreters: optical diffraction effects and aber-
rations, focussing, electronic noise, image motion, atmospheric perturba-
tions, chromatic aberrations, vignetting etc. Radiometric restoration aims
at the elimination of these perturbations using a-prior? information derived
from sensor calibrations prior to actual imaging, or posteriori informations
derived from imagery already taken of test objects.
Image restoration serves to relate the image densities to the energy
used to produce the object's image. It attaches thus a quantitative value to
the images and is a pre-requsite to quantitative data analysis based on image
gray values.
Figure 1: Aircraft scanner image of Red Mountain, Arizona; (a) with
coherent noise; (b) after noise removal; (c) after geometric correc-
tion for panoramic distortion; (d) after low frequency notch filtering
to reduce shading.
Filtering may be considered the essential restoration tool. Generally,
filtering is visualized in terms of spatial frequencies. Noteh filtering,
i.e. the reduction or removal of specific frequency components, can be
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