Photogrammetric Record, 13(76): 493-504 (October 1990)

DIGITAL IMAGE PROCESSING IN PHOTOGRAMMETRY

By D. J. BETHEL formerly with Kern and Co. Limited, Aarau

(Paper read at the Technical Meeting of the Society on 17th October, 1989)

Abstract This review of digital image processing refers to the pioneer work of

Helava and Hobrough which has influenced the most recent trends in photogrammetry. The author goes on to discuss aspects of digital image acquisition, storage and display, as well as digital photogrammetric procedures and systems.

INTRODUCTION OVER 30 years ago, there were a couple of clever fellows who put forward some ideas in our field of photogrammetry. In 1957, U. V. Helava invented the analytical plotter and in 1959, G. L. Hobrough described the Stereomat with its far reaching implications for automation in photogrammetry. These ideas formed the structure of today’s and tomorrow’s photogrammetric techniques.

The analytical plotter, proposed in 1957, had its first public version introduced in 1964. It started to appear at the International Society for Photogrammetry (ISP) Congress in 1976 and by 1980, in Hamburg, the analytical plotters presented were the main focus of the ISP exhibition. By the mid 198Os, they were in common use in mapping establishments. The development of the analytical plotter followed closely the developments in computing, making use of microcomputers and distributed processing as they became available. In photogrammetry, analytical instrumenta- tion has been developed and analytical techniques accepted. The analytical plotter has reached maturity and anyone talking about a stereoplotter nowadays assumes an analytical plotter.

In the case of automation, which is where our hopes for digital photogram- metry lie, matters have not progressed so smoothly. Helava (1 978), considering digital components in photogrammetry, proclaimed:

With ones and zeros and nothing more, The computer handles any chore. When filled with pixels, It really excels And produces maps galore.

We are a long way from the goals of automated mapping, already outlined in the 1950s (Hobrough, 1959). However, rapid advances in sensor technology in recent years have provided us with a number of options as to how to obtain our pixels, and improvements in computer hardware and software are providing us with better tools to deal with the pixels once we have them.

In this paper, we will consider some of the aspects of digital images and digital image processing in photogrammetry. Several names have been proposed for this mixture of technologies, such as videogrammetry and digital image photogram- metry, but we seem to be reaching a consensus that this topic is named digital photogrammetry. Digital photogrammetry may be defined broadly as the field of three dimensional information extraction from stereoscopic or multiple digital image coverage of objects. We will look from a photogrammetrist’s point of view at

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(a) data acquisition; (b) data storage and visualisation; (c) digital photogrammetric procedures; and (d) digital photogrammetric systems.

In general, differentiation will be made between two different types of digital photogrammetric techniques, namely real time digital photogrammetric processes, where the imagery is captured and partially or fully processed in real time within today’s standard video rates of 1/25 s or 1/30 s depending on which video standard is used, and digital photogrammetric processes which are not camed out in real time and where the imagery is captured and processed at speeds other than standard video rates.

DIGITAL IMAGE ACQUISITION Scanner technology has blossomed during the 1980s. Electron beam sensors

have given way to solid state sensors and, in particular, to charge coupled device (CCD) sensors.

Imaging tubes have some advantages over CCD sensors since lower light levels are required and they have high resolution capabilities. However, due to higher versatility and geometric stability, CCD solid state sensors, in areal or linear formats, are primarily used in photogrammetric applications. The application of sensors to render a digital image of an object is either a direct application, where the sensor directly scans the object in question (for example, the SPOT (Satellite pour I’Observation de la Terre) satellite scanning the earth) or an indirect application, where an intermediate image of the object is scanned (for example, a CCD camera scanning aerial photography).

CCD Scanner/Sensor Photons of light strike the sensor elcments or pixels (formed from the two

words picture and elements) and generate a charge in each cell (Fig. 1). The sensor pixel spacing varies between about 8 pm and 30 pm and often the pixels are rectangular rather than square, as the horizontal and vertical construction of the sensor differs. The charges created by the photons are transferred and measured by converting the analogue signals into digital quantities. Some pixel processing may be camed out by the CCD device to correct for sensor distortions and loss of information during transfer.

Control of illumination is very important when using CCD sensors either when directly imaging an object or when indirectly converting the object to digital form from a previous analogue storage device.

CCD Areal Sensors CCD areal sensors are formed by a frame, or matrix, of sensor elements. They

are commonly called digital cameras but, in effect, the signals sensed and transferred are analogue signals, which are then transformed into a digital value. The sensed analogue values are scanned by the device and transferred to analogue to digital converters to produce the digital values. Configurations allowing the entire frame of sensor signals to be transferred to the analogue to digital converters at one time are called frame transfer devices, while devices which transfer the analogue signals one line at a time are called interline transfer devices (Fig. 1).

Frame transfer devices allow the sensor to have a smaller possible pixel resolution, with no gaps between the pixels, but there is a danger of loss of signal due to the charges being held longer before being converted to digital values. Interline transfer results in loss due to transfer times but necessitates larger sensor areas, with gaps between the lines of pixels. Today, there is not much difference between the results from the two types of sensor but the trend is towards frame devices.

At present, most CCD areal sensors used in photogrammetry have real time capabilities. The restrictions of video rates are imposed which thus limit the

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number of pixels which may be sensed and sampled during one video cycle to a matrix of approximately 500 x 500 pixels. Larger coverage has been obtained by coupling multiple sensors together. Other areal CCD sensors do exist however (such as Videx 1000 x 1000 pixels and Tektronix 2048 x 2048 pixels) but the scanning rate is slower than the smaller size CCD cameras. Areal sensors are being used in both direct and indirect methods. In systems where the object is directly observed by area sensors, resulting values (three dimensional co-ordinates) may be obtained in real time.

Areal CCD sensors, which have been fitted to analytical plotters to convert the photographic image into digital form, are employed in an indirect mode as they scan an analogue representation of the object rather than the object of interest itself.

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CCD Linear Sensors In the fields of photogrammetry and remote sensing, we have been familiar for

some time with CCD linear sensors. There are no real time linear systems at present as the rates of scanning and transferring the data are too slow to be regarded as real time. Both direct and indirect applications of linear scanners are being used in a non-real time environment. These scanners have a variety of dimensions and configurations linking more than one scanner together.

Satellite linear arrays directly scan the earth and transmit digital data back to earth, as with SPOT and MOMS (Modular Opto-electrical Multispectral Scanner). Some scanners have been developed for use in aircraft but, as yet, they are not widely used (for example, the Multi-detector Electro-optical Imaging Scanner (MEIS)).

Indirect methods of obtaining digital images are carried out by digitising photographs of the objects of interest. There are a number of such scanners available but, at present, none are really designed for photogrammetric require- ments so as to consider factors of format, speed and cost. Scanners range from small desktop systems which generally digitise with resolutions too coarse for our purposes (for example, Agfa and Rank Xerox) to larger expensive systems more complex than we require (for example, Scitex and Hell).

DIGITAL IMAGE STORAGE AND DISPLAY In photogrammetry, our traditional medium for storing information about the

object of interest is the photograph. With digital photogrammetry, the medium is the digital image. The digital image may be treated in a variety of ways. At one extreme, the required information may be extracted as the digital information is obtained with the digital image being discarded while, at the other, the information may be processed once the entire digital image has been obtained.

In most real time applications, the digital imagery is not stored. The digital information covering the area of interest of the object is captured, processed and analysed within the required time frame, with or without displaying images, and then discarded. In non-real time applications, one of the main characteristics and headaches of digital photogrammetry involves the vast quantities of data which must be stored. For example, each SPOT panchromatic scene contains 36Mbytes of data and an aerial photograph digitised at 20 pm generates lOOMbytes of data. Hardware advances will help us deal with these quantities of information more easily and economically in the future but, at the present time, we have to balance between either employing large mass storage devices or, alternatively, working with subsets or subsamples of larger images.

As the reliable automation of our photogrammetric processes is still lacking somewhat, the digital imagery which is collected may need to be displayed to allow measurement and interpretation of information and also to verify results obtained automatically. Images may be displayed and possibly measured on a variety of display screens ranging from personal computers to high resolution monitors. For simple interpretation and verification, it may suffice to view the digital images monoscopically but, when three dimensional geometric information is to be checked or measured, a stereoviewing capability is necessary. At present, the options available for stereoviewing are similar to those which have been used on analogue stereorestitution instruments in the past and include anaglyphic filters, polarising systems and binoculars.

The anaglyphic filter principle may be applied by displaying the left and right image in a monitor using complementary colours, usually red and green. The stereomodel is seen by viewing the monitor through glasses with the appropriately coloured filters covering the eyes. A polarising system may be effected for digital imagery by placing a liquid crystal shutter in front of the monitor with the left and the right image being alternately displayed and polarised. The user wears glasses with polarising filters to see stereoscopically. Lastly, a familiar binocular viewing system may be mounted and the left and right image independently presented either by using two monitors or displaying both images on one monitor which has split

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screen capabilities. While the binocular system was the clear favourite in analogue instrumentation, it is too early to determine which, if any, of the these techniques will endure for viewing digital imagery.

DIGITAL PHOTOGRAMMETRIC PROCEDURES Digital image processing has been implemented in photogrammetric proce-

dures to automate operator intensive, tedious tasks, to ease measurement procedures for non-photogrammetrists and to produce more cost effective and reliable information extraction solutions. In addition to aiding or replacing traditional photogrammetric techniques, digital image processing has been imple- mented to provide new possibilities not previously available. The main goal however is the same as always, the extraction of semantic and three dimensional geometric information.

Scanning Scanning of photography is taking place to convert images previously stored in

analogue form to digital form, in order to apply further digital image processing techniques, or to combine them with existing digital information.

Image Enhancement and Image Transformation Digital images may be further processed using techniques of resampling,

filtering and conversion to influence the geometry and radiometry of the images. Resampling of pixels may be used to apply geometric transformations to the imagery to correct for sensor calibration, sensor orientation and sensor platform orientation, resulting in digital orthophotography. Resampling, filtering and conversion 'of pixels may be used to improve and enhance the radiometric properties of the images to allow easier information extraction and the production of a more attractive image.

Pattern Recognition Identification of known, well defined targets has been implemented using

correlation computations. In photogrammetry, this is used for the automation of instrument calibration by automatic grid plate measurement, inner orientation by measurement of fiducial marks, absolute orientation by measurement of targetted control points and aerial triangulation by measurement of targetted tie points.

Image Matching Automatic matching of stereo-images for the extraction of geometric informa-

tion has been the centre of much research in recent years. Matching techniques have been implemented in relative orientation to determine x and y parallaxes between images, in absolute orientation to match defined control points, in aerial triangulation for automatic tie point selection and transfer and also in digital terrain model (DTM) collection to determine the heights of specific or non-specific points. The matching methods which have been developed and investigated in the photogrammetric field are primarily

(a) cross correlation coefficient; (b) least squares matching; (c) cross correlation with geometric constraints (vertical line locus (VLL)

(d) feature based matching with least squares matching (Foerstner, 1986); (e) least squares matching with geometric constraints (adaptive least squares

(f) feature based matching with adaptive least squares matching;

method);

matching (ALSM) (Gruen and Baltsavias, 1986));

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(8) multipoint matching (Rosenholm, 1986); (h) feature based matching with multipoint matching; (i) dynamic programming with least squares matching (Koelbl et al., 1987);

(j) facet matching (Wrobel, 1987). As is evident from this array of methods, no clearly superior solution has been

found and the results of a particular method may vary depending on the circumstances under which it is applied. The most popular methods at present use feature based matching techniques to provide a coarse initial match between images, after which some form of least squares matching is applied to produce an accurate, subpixel match of images. Matching has mostly been applied to photograph pairs, but some excellent results have come from using multiple image solutions. Success in image matching has been achieved but there are still no hard and fast rules as to which procedures should be used under which conditions. Some very reliable strategies are emerging (Hannah, 1988) and the effort in the future will be based more on defining those strategies by which the photogrammetrist can use these matching tools in either an automatic or semi-automatic manner.

and

Feature Extraction Feature extraction has been attempted to a limited extent, mainly by

introducing filters to highlight points and lines and to help identify discontinuities for image matching.

Image Analysis We are just beginning to apply image analysis techniques to our complex

images (Foerstner, 1989). Only by looking at other areas, such as computer vision technology, where vision systems are being developed can we hope to find some basis for our investigations. However, the basic theory of computer vision is still incomplete.

The basic stages in image analysis are digital image processing, feature extraction and image understanding. There is still some way to go before we can build up the features which we extract to become identifiable objects and even further to general analysis of the image.

DIGITAL PHOTOGRAMMETRIC SYSTEMS A number of real time experimental systems have been proposed and

developed within the photogrammetric community, but none are as yet available commercially (such as Mapvision from the Technical Research Centre of Finland (Haggrh, 1986); Digital Photogrammetric Station (Versions I and 11) from the Institute of Geodesy and Photogrammetry, ETH Zurich (Gruen, 1988); and National Research Council of Canada (El-Hakim, 1986)).

Some digital photogrammetric workstations for non-real time applications are in existence already and an International Society for Photogrammetry and Remote Sensing (ISPRS) Working Group has been created between ISPRS Commissions I1 and I11 to investigate the requirements and specifications for such systems.

General digital workstations which are available commercially include: (a) DMS desktop mapping system from Erdas; (b) DSPl digital stereophotogrammetric system from Kern (Fig. 2) (Cogan et

(c) Pegasus system from Autometric (Molander and Otto, 1989); (d) ContextMapper from ContextVision (Lohmann et al., 1988); and (e) T10 digital station from Matra (Euget and Vigneron, 1988).

al., 1988; Cogan and Hunter, 1989);

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FIG. 2. Kern DSPl digital stereophotogrammetric system.

Some specialised digital systems which are available commercially include: (a) DCCS digital comparator correlator system from HA1 (Helava, 1987)

\-lhich provides automatic identification and measurement of tie points for serial triangulation;

(b) Eudicort Orthophotosystem from Eurosense which allows the generation of digital orthophotomaps; and

fc) Automatic Topographic Mapper from Geospectra which enables genera- tion of digital terrain models from SPOT imagery.

Experimental non-real time systems have also been developed, most notably in educational institutions such as University College London (Gugan and Dowman, 1986; Muller, 1989), the Technical University of Berlin (Koenig et al., 1988) and Lava1 University, Quebec (Agnard et al., 1988).

CONCLUSIONS The products resulting from digital photogrammetry are, as ever, planimetric

and possibly height co-ordinates of objects, together with some semantic informa- ti00 concerning the objects. The form of the products may differ from traditional photogrammetric vector .based output in that they tend towards raster based information (for example, scanned images, digital orthophotographs, DTMs and combinations of these products such as three dimensional perspective views and scene simulation). However, vector information will still play a key role with the combination of raster and vector data becoming commonplace. Our field is ever increasingly dependent on the computer hardware and software development in geographical information systems (GIS) and image processing technologies. Developments in these areas will enable us to define more precisely the photogrammetric products of the future and provide more cost effective solutions to the challenge of data collection and analysis.

We have just touched the tip of the iceberg of the potential of digital photogrammetry. The prospects for the future look extremely interesting but the enormity of the tasks which lie ahead are not to be underestimated, tasks such as integrating image matching techniques into practice and laying the foundation

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stones for image analysis. There is plenty of work for us to do, in case it is feared that our posts are being swallowed up by the image processors! Indeed

GIS we need to feed. For real time measurement there is the need. Don’t despair! We are there: Photogrammetrists will do the deed.

Neither Helava nor the present author would ever receive any prizes as bards but, with the interesting developments in our field today, it is better to remain an enthusiastic photogrammetrist.

REFERENCES

AGNARD, J. P., GAGNON, P.-A. and NOLETTE, C., 1988. Micro computers and photogrammetry. A new tool: the Videoplotter. Technical Papers ACSM-ASPRS Annual Convention, St. Louis, 3: 1-6.

COGAN, L., GUGAN, D., HUNTER, D., LUTZ, S. and PEW, C., 1988. Kern DSPI-Digital Stereo Photogrammetric System. International Archives of Photogrammetry and Remote Sensing, 27(2):

COGAN, L. and HUNTER, D., 1989. Digital image photogrammetry and the Kern DSPI. Technical Papers ACSM-ASPRS Annual Convention, Baltimore, I: 39-46.

EL--, S. F., 1986. A real-time system for object measurement with CCD cameras. International Archives of Photogrammetry and Remote Sensing, 26(5): 363-373.

EUGET, G. and VIGNERON, C., 1988. Matra Traster TlON digital stereoplotter. Ibid., 27(2): 117-125. FOERSTNER, W., 1986. A feature based correspondence algorithm for image matching. Ibid., 26(3/3):

FOERSTNER, W., 1989. Image analysis techniques for digital photogrammetry. Proceedings of the 42nd Photogrammetric Week, Stuttgart. 342 pages: 205-22 1.

GRUEN, A. W. and BALTSAVIAS, E. P., 1986. High precision image matching for digital terrain model generation. International Archives of Photogrammetry and Remote Sensing, 26(3/1): 284-296.

GRUEN, A,, 1988. Towards real-time photogrammetry. Photogrammetria. 42(5/6): 209-244. GUGAN, D. J. and DOWMAN, I. J., 1986. Design and implementation of a digital photogrammetric system.

International Archives of Photogrammetry and Remote Sensing. 26(2); 100-109. HAWREN, H., 1986. Real-time photogrammetry as used for machine vision applications. Ibid., 26(5):

HANNAH, M. J., 1988. Digital stereo image matching techniques. Ibid., 27(B3): 280-293. HELAVA, U. V., 1978. Digitale Komponenten in der Photogrammetrie. Proceedings ofSymposium ueber den

Einsatz digitaler Komponenten in der Photogrammetrie, Hannover. Inst. fur Photogrammetrie und Ingenieurvermessungen, TU Hannover. 2: 23 pages.

HELAVA, U. V., 1987. Digital Comparator Correlator System (DCCS). Proceedings of Infercommission ConJerence on Fast Processing of Photogrammetric Dafa. Interlaken. 437 pages: 404-41 8.

HOBROUGH, G. L., 1959. Automatic stereo plotting. Photogrammetric Engineering, 25(5): 763-769. KOELBL, O., BOUTALEB, A. K. and PENS, C., 1987. A concept for automatic derivation of a digital terrain

model with the Kern DSR 11. Proceedings of Intercommission Conference on Fast Processing oj Photogrammetric Data. Interlaken. 437 pages: 306-3 17.

KOENIG, G., NICKEL, W. and STORL, J., 1988. Digital stereophotogrammetry-experience with an experimental system. International Archives of Photogrammetry and Remote Sensing, 27( 10):

LOHMANN, P., PICHT, G., WEIDENHAMMER, J., JACOBSEN, K. and S K ~ , L., 1988. The design and implementation of a digital photogrammetric stereoworkstation. Ibid., 27(9): I1 155-11 164.

MOLANDER, C. W. and OTTO, J. F., 1989. Digital terrain model data extraction and editing on the Pegasus softcopy workstation. Technical Papers ACSM-ASPRS Annual Convention. Baltimore, 2: IS 1-161.

MULLER, J.-P. A. L., 1989. Real-time stereo matching and its role in future mapping systems. Survey and Mapping 89. Paper C5: 15 pages.

ROSENHOLM, D., 1986. Accuracy improvement of digital matching for evaluation of digital terrain models. International Archives of Photogrammetry and Remote Sensing, 26(3/2): 573-587.

WROBEL, B. P., 1987. Facets stereo vision (FAST Visionba new approach to computer stereo vision and to digital photogrammetry. Proceedings of Intercommission Conference on Fast Processing of Photogram- metric Data. Interlaken. 437 pages: 231-258.

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Rksumk L’auteur procede h l’examen des traitements d’images numkriques, en

se rkflrant au travail de pionnier qu’ont effectuk Helava et Hobrough et qui ont injluenck jusqu’aux plus rkcentes tendances que l’on constate en photogrammktrie. L’auteur analyse ensuite divers aspects concernant la saisie, l’archivage et l’aflchage des images numkriques, ainsi que les mkthodes et les systemes de photogrammktrie numkrique.

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Zusammenfmsung Dieser Uberblick zur digitalen Bildverarbeitung bezieht sich auf die

Pionierarbeiten von Helava und Hobrough, die die jungsten Trends in der Photogrammetrie beeinjlujt haben. Dann behandelt der Autor Aspekte der digitalen Bilderfmsung, -speicherung und -darstellung und diskutiert digi- tale photogrammetrische Verfahren und Systeme.

DISCUSSION Mr. A. S. Macdonald (Chairman): Thank you very much, Mrs. Bethel. Let’s

hope that we see that poem in The Photogrammetric Record in due course! I found that a very lucid exposition of the frontiers of technology and digital photogramme- try. I am sure that there are going to be some questions.

Mr. Newby: It’s all very alluring. I think we are very excited about these prospects, but are we going to be able to afford them? Are they actually going to work for us, help us to sell more maps and make them more cheaply?

Mrs. Bethel: We have a theoretical base for image matching. Now the emphasis is on finding the correct strategies and hardware to implement the techniques in a cost effective manner. I would hazard a guess that within two to three years some of the aspects of image matching will be used on a production basis.

However, feature extraction and image analysis still have a long way to go, because the basic foundations of these techniques are not yet established. In the next three to five years and beyond, the emphasis in research will be on this topic and gradually techniques will begin to emerge. Until we have a basis in the area of image extraction and analysis,we can’t say too much about the cost effectiveness.

Mr. Newby: Do you think that when we grasp the tip of the iceberg with both hands we won’t catch cold?

Mrs. Bethel: I shouldn’t think so, but we have to take advantage of these emerging techniques. We could stay safe and twiddle the handles of our AS ad injnitum, but sometimes we have to be a little daring, as I think the Ordnance Survey is just now, with the introduction of Helava’s DCCS equipment.

Mr. Proctor: I would like to make three brief comments. Firstly, Mr. Newby asks whether we can afford digital image processing; 20 years ago we thought we could not afford digital plotters, but now if you could buy a first order analogue plotter it would cost more than the equivalent digital version. The same trend seems likely to apply. Secondly, I certainly support Mrs. Bethel’s remarks on real time applications. The computing and data processing problems will be severe for applications such as robotics and industrial process control. The need for a very rapid response means, for instance, that the strategy for image matching must be very efficient and reliable. Thirdly, and finally, I noted that Mrs. Bethel’s introduction traced the chronology from about 30 years back. By coincidence it was about then that the term “aerial triangulation” ceased to describe, adequately, the computational aspects of photogrammetry; both “analytical photogrammetry” and “digital photogrammetry” had their supporters and it is fortunate that the former was generally adopted or else there would now be some confusion.

Mr. Farrow: Have you any idea just how much of this extra information content the image analysis is going to enable you to obtain from the imagery? The photographic process is a snapshot of gaining information and once it’s left the laboratory, you’re not going to extract any more information other than what can be seen with the human eye. With image processing techniques, it is possible to extract information that you wouldn’t otherwise be able to obtain. Do you have any feel for the gains there are to be obtained from that approach? Using poor imagery which you might otherwise reject, allied to image processing techniques, you can actually begin to extract some information.

Mrs. Bethel: There are two or three different stages here. One is simply being able to enhance your photographic images by putting them into digital form, applying some image processing and then to proceed with operator measurement.

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The second is to apply some filters such that certain features, such as points or lines, could be highlighted and then features may be matched automatically or measured by an operator. The third aspect is that of applying image analysis and in this area much development is required before we can estimate the gains in using image processing.

Mr. Farrow: Are people working on using the existing vector information of the objects that appear in the photographs? In our particular interest, we are doing map revision. We already know where a significant number of features are and what they are. Can one not use that information to teach the system something? Will that make its analysis that much easier?

Mrs. Bethel: In computer vision, a lot of work has been done in this area, but in photogrammetry we have just started. For example, Foerstner IS now changing his emphasis from image matching to image analysis. He is using predefined radiometric and geometric characteristics of features to help extract not only the elements of an object, such as lines and points, but also to identify the formation of the elements, such as house or circle. The better the parameters of the object can be defined, the more chance there is of extracting that feature. It will be some time before the basis is there which will be useful for us.

Mr. Murray: Just on that point of time, earlier this year Mr. Newby and I were speaking to Professor Foerstner and he said that we would never see the realisation of those techniques in our lifetime. I don’t know about Mr. Newby, but I would like to see them achieved. Have you any comments on that?

Mrs. Bethel: One of the problems is that it seems a very easy task because we can all sit down at a machine and extract information, but it is really a very complex problem. Researchers are going right back to the basic level of trying to study how our eyesight works in order to be able to apply these techniques for information extraction and recognition. I would be happy to see matching techniques widely implemented in the next five to ten years, with some help in semi-automation under operator guidance. I don’t see within our working lifetime that we’ll be able to place a photograph in one end of a machine and a sensible map will come out at the other end. It is important that we keep trying these new semi-automatic techniques to help develop useful strategies which may be of aid to photogrammetrists and ease the introduction of photogrammetric techniques in disciplines where there are no trained operators.

Chairman: You mentioned the question of plotting by a completely unskilled (unskilled in the photogrammetric sense) person who could buy in photography that had been controlled in some way, set it up in something like a DSPl and extract any of that mass of information that, say, the Ordnance Survey hasn’t taken out of the photograph and chosen to put on its maps. This may be of great interest to an individual professional dealing with the land. A forest manager could keep an inventory up to date without any further assistance from the Ordnance Survey once he had the underlying landscape. But would he ever be able to afford to do that? I think that we return to the earlier question of cost. Would a DSPl ever be cost effective if you just have it on the comer of the desk and use it once a month when you have a need. It’s a nice concept, but is it ever going to be reality? That’s what one wonders.

Mrs. Bethel: There are a couple of points here. More research is needed to define what information we want to put in and obtain from geographical information systems (GIs). All the necessary information may exist in a data base in the form of raster and/or vector data but the knowledge required has not yet been extracted.

The information to be extracted by some users may not necessitate a DSP type of solution. For example, subsampled images may be used resulting in lower accuracy but also requiring less storage capacity. Also, not all users need to have real time movement of the images, so this feature could be eliminated and less sophisticated hardware used. Once we can identify clearly what is the knowledge which we wish to extract from our GIS data bases, then we can define more precisely the procedures to obtain this information and provide the specific tools to do the work.

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Mr. Peak: Could you comment on the relative resolution of CCD cameras, compared with conventional aerial photography?

Mrs. Bethel: The latest CCDs used at Kern have a pixel size of 9 x 1 1 pm. Tests have been camed out by various people to determine what pixel size should be used to digitise aerial photography, maintaining the geometric and semantic informa- tion. The conclusions were that a pixel size of 20 pm to 25 pm is required to produce results similar to an analytical plotter.

With advances in aerial photography, such as better films and forward motion compensating cameras, perhaps more tests should be carried out to see if this pixel size is suficient, but it appears that around the 20 pm pixel size will represent the content and geometric information we have in our photographs.

Dr. Dowman: To return to the previous point which was made by the Chairman about people being able to afford the DSP, surely the answer to this is that they won’t. I was going to ask Mrs. Bethel whether she thinks that perhaps the concept of a large photogrammetric instrument is already out of date. In fact, you will have a workstation on your desk which will perform a number of tasks but it will have a package which will carry out stereophotogrammetry. With scanning digitisers now becoming cheaper, you would digitise your photograph as you need, do what you want to do with it on the workstation and add the data to the database rather than have this expensive photogrammetric instrument in occasional use.

Mrs. Bethel: Yes, there will be little demand for an expensive piece of equipment capable of doing much more than the individual requires. When users can define what information they wish to extract from the CIS for their particular application, then we can develop the systems which are tailored for these needs.

Mr. Newby: Once you’ve given us a device that will enable us to obtain a DTM for the whole country quickly and cheaply, perhaps we can throw away the expensive stereophotogrammetric equipment and only digitise monocularly. But there’s a transitional stage to overcome and that must not be too expensive.

Mrs. Bethel: I think there is always going to be a case where stereoscopy is useful for interpretation purposes if not for the actual measurement. Before DTMs of a whole country are produced, specifications of what is required must be made, or facilities must still exist for augmenting the data later, such as capturing the heights of the top and bottom of buildings in urban areas.

Mr. Newby: We are certainly thinking about that at the moment. Mr. Furrow: How good are correlation algorithms nowadays for solving these

problems of man-made structures at large scale where their size is of significance in relation to the general height variation?

Mrs. Bethel: The algorithms are terrible. There are none of them that work individually, or at least show a superior solution. What does work are some of the strategies being proposed, often using combinations of algorithms, and some excellent reports have been produced. One of the best lately was a paper from Hannah (1 988). In general, the trend is to use some kind of filter to extract edges. Usually where there is an edge, there is a break in the terrain. These edges can be used to define areas within which you can correlate and then build areas of these correlated patches. This is where existing information could be incorporated, such as using measured boundaries or houses, as a basis for the DTM.

Mr. Phillips: The digital images which you showed us were monoscopic images so presumably their greyscales were measured at one wavelength. Does the image matching and feature recognition become easier if you introduce colour?

Mrs. Bethel: I am not familiar with tests on colour imagery. Mostly in photogrammetry, we use black and white photography because of its better geometric properties.

Mr. Phillips: A lot of our photogrammetry is easier when we use colour for close range and underwater objects.

Mrs. Bethel: Yes, for interpretive purposes. It could be that colour imagery is useful during image analysis, but it is too early to say.

Mr. Taylor: In the move from analogue to analytical photogrammetry attempts were made to adapt analogue instruments to transform them into analytical photogrammetric instruments. Is there an intermediate step where we can take

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today’s analytical instrumentation and carry out a conversion incorporating correlation without going through the great expense of the DSP?

Mrs. Bethel: By fitting CCD cameras to analytical plotters, some semi- automatic processes could be implemented. This will also enable us to use some of the advantages of image processing techniques being developed in photogrammetry with our existing equipment instead of investing in a totally digital station.

Chairman: It remains for me to thank Mrs. Bethel for a very professional lecture about these interesting frontiers of technology. Thank you for coming here and giving us that very good lecture. I would like to offer you, on behalf of all Society members, our rather delayed congratulations on your mamage and also to give you our very best wishes because I understand that you are about to leave Kern and start a new life in America with your husband. I hope all that goes very well. I’m sure that the Kern Company is very disappointed; having listened to you tonight, I know that Kern will feel the loss of your services very keenly indeed. We are delighted that we caught you before you left for the distant shores of America.

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