pport a 
Ver is 
ics in 
eye is 
igure), 
tential 
> image 
lor in 
reefold 
1j). On 
, false 
casting 
.h more 
lor CRT 
ch may 
Color 
lution 
Ling in 
1Ised in 
photo- 
photo- 
ligital 
ced by 
le and 
aerial 
on and 
th the 
tes. 
essed, 
de and 
e will 
ta and 
in the 
ds. À 
> data 
aerial 
multi 
in one 
e of a 
of a 
5. 
4. DIGITAL VIDEO RATE PROCESSING 
  
The issue in electronic image processing and analysis is speed. This is 
so whether it is to process large images of several thousand pixels square 
in a reasonable time, or TV size images in real-time. Only a few processing 
algorithms are "single point" (one arithmetic operation per pixel); ones 
such as addition and subtraction, or code conversion as with look-up table 
transformation. More interesting and powerful ones such as neighborhood, 
transform-domain, statistical, and morphological operations require several, 
tens, possibly hundreds, of arithmetic operations per pixel. The 
traditional Von Newmann general purpose computers are woefully inadequate 
for the demands modern image processing impose, although they can perform as 
control hosts in digital image systems. The "minisupercomputer" promises 
help at the high end of the power spectrum for photogrammetric image 
processing while special processors (different configurations of array and 
parallel processors) are also emerging with a range of capabilities. 
Progress in parallel systems, Hung, 1984, Lerner, 1985, Meng, 1986, becomes 
more essential when it is realized that the speed increase provided by 
improved hardware technology is only running at about a factor of two every 
four years, Manuel, 1986. Confounding the progress in parallel architecture 
however is a relatively sluggish advance in parallel software, Wolfe, 1986. 
Image processing algorithms which are repetitive present little problem, but 
related applications involving artificial intelligence are difficult to 
decompose and are very application dependent, Charniak, 1985, Wolfe, 1986. 
4.1 Towards the Cost Effective Supercomputer 
It is difficult to believe ten years have passed since Seymour Cray 
ushered in the era of the supercomputer. A new generation of minisuper- 
computers is emerging to fill the large gap between the Cray level of super- 
computer and the superminicomputer. Formerly restricted to such 
applications as weather prediction and weapons research, small-scale 
engineering projects are expected to benefit from the coming 
minisupercomputer boom. Photogrammetric image processing, particularly of 
large data bases, can evolve by planning to integrate powerful computers 
into future systems. As Table 1 shows, a race is developing to build 
smaller, low cost supercomputers. 
Table 1. Examples of High Performance Computers, (Ohr ‚1 1986) 
  
  
  
Computer MFLOP's*  |Price (approx.) Designation 
Cray X/MP 700 $10Million Supercomputer 1 
Cray-1 300 5M Supercomputer 1 
Intel iPSC-VX/d6 424 0.85M Supercomputer 
FPS-T-10 128 0.5M Supercomputer 
FPS-T40000 (262,000) (200 M) (Proposed) 
Alliant FXB 90 1M Minisupercomputer 1 
IBM 3090 15 3M Minisupercomputer 1 
FPS-5000 60 0.15M Minisupercomputer 1 
DEC 8800 3 0.6M Superminicomputer 1 
DEC VAX 8650 1.5 0.7M Superminicomputer 1 
  
  
  
  
*Millions of floating point operations per second, (64 bits). 
91