SATELLITE IMAGERY FROM ACQUISITION PRINCIPLES OF . Delai:3 semaines CPD215

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This book was written for students and engineers wishing to understand the basic principles behind the acquisition of optical imagery for Earth observation and the ways in which the quality of the images can be optimised.

Intended both for designers and downstream users, the book begins with a detailed explanation of the physical principles involved when a satellite acquires an optical image and then goes on to discuss image processing and its limits as well as the ultimate performance obtained.

It also covers in depth the problems to be solved when designing and dimensioning observation systems so that the reader can become familiar with the various processes implemented for acquiring an optical image.

The book describes a very wide range of subjects from fundamental physics (radiation, electronics, optics) to applied mathematics (frequency analysis), geometry and technological issues.

It draws on work done over many years by engineers from CNES (the French Space Agency), the IGN (the French National Geographic Institute) and ONERA (the French Aerospace Laboratory) in the field of satellite optical imagery.

I. INTRODUCTION

Philippe LIER (CNES), Christophe VALORGE (CNES)

I.1. Some history

 I.2. What is remote sensing?

    I.2.1. Definition

    I.2.2. What is a 'digital image’?

    I.2.3. What is 'Image Quality’?

    I.2.4. Ground processing to correct for remote-sensing effects

 I.3. Some examples of Earth observation applications

    I.3.1. Meteorology

    I.3.2. Mapping

    I.3.3. Intelligence gathering

    I.3.4. Monitoring natural disasters

    I.3.5. Scientific applications

 I.4. A panorama of several Earth observation missions

    I.4.1. The KEYHOLE satellites of the CORONA programme

    I.4.2. The Landsat family, example: Landsat 7

    I.4.3. The SPOT family

    I.4.4. PLEIADES

    I.4.5. American commercial satellites

    I.4.6. Vegetation

    I.4.7. POLDER

    I.4.8. ScaRaB

    I.4.9. CALIPSO’s Infrared Camera

 I.5. Scope of this book

II. IMAGE GEOMETRY

Jean Marc DELVIT (CNES), Daniel GRESLOU (CNES), Sylvia SYLVANDER (IGN), Christophe VALORGE (CNES)

II.1. Introduction

    II.1.1. Chapter outline

    II.1.2. Introduction to direct location

 II.2. Pre- requisites: Space and Time Reference frames

    II.2.1. Stating the problem

    II.2.2. Reference frames and object-centred coordinate systems

II.2.3. From the Earth to the stars

    II.2.4. Space reference frames

    II.2.5. The time references

    II.2.6. Changing reference frames

 II.3. Geometric principles of acquisition

    II.3.1 The different types of sensor

    II.3.2. Time-stamping images

    II.3.3. Satellite orbits

    II.3.4. Satellite attitude

 II.4. Geometric modelling of the scene

    II.4.1. General principle

    II.4.2. Review of conic geometry

    II.4.3. Physical modelling of the scene

    II.4.4. Analytical modelling of the viewing geometry

    II.4.5. Refining the geometric viewing model

 II.5. Geometrical processing

    II.5.1. Geometrical corrections

    II.5.2. Image matching and correlation

    II.5.3. 'Downstream' geometric processing

 II.6. Geometric image quality

    II.6.1. Introduction

    II.6.2. User requirements and GIQ

    II.6.3. In-flight geometric image quality

    II.6.4. Summary of requirements and GIQ performance

 II.7. Essential geometrical formulations

    II.7.1. Notations

    II.7.2. Basic formulae

    II.7.3. Detector projection

 II.8. Bibliographical references

III. RADIOMETRY

Alain BARDOUX (CNES), Xavier BRIOTTET (ONERA), Bertrand FOUGNIE (CNES), Patrice HENRY (CNES), Sophie LACHERADE (ONERA), Laurent LEBEGUE (CNES), Philippe LIER (CNES), Christophe MIESCH (ONERA), Françoise VIALLEFONT (ONERA)

III.1. Introduction

 III.2. Measurement physics

    III.2.1. Introduction

    III.2.2. Definition of radiative parameters

    III.2.3. Optical properties of surfaces

    III.2.4. The atmosphere

    III.2.5. Analysis of radiance at sensor level

III.3. Acquisition principle: description of the on-board   imaging system

    III.3.1. Introduction

    III.3.2. Optics

    III.3.3. Detector system

    III.3.4. Electronic system

 III.4. Mathematical model of the image acquisition system

    III.4.1. Calculation of irradiance over the focal plane

    III.4.2. Calculating the number of electrons produced

    III.4.3. Calculating the output signal expressed in digital counts

 III.5. Radiometric modelling of the image acquisition process

    III.5.1. Introduction

    III.5.2. Example 1: IIR CALIPSO radiometric model

    III.5.3. Example 2: the SPOT radiometric model

    III.5.4. Example 3: the PLEIADES-HR radiometric model

    III.5.5. Example 4: the POLDER radiometric model

 III.6. Calibration and measurement of radiometric performance

    III.6.1. Introduction

    III.6.2. Relative calibration in the field of view, or 'normalisation'

    III.6.3. Absolute calibration

 III.7. Radiometric resolution

    III.7.1. Introduction

    III.7.2. Example: PLEIADES radiometric noise model

    III.7.3. Estimation of instrument noise

 III.8. Summary and future prospects

 III.9. References

IV. IMAGE RESOLUTION

Sébastien FOUREST (CNES), Philippe KUBIK (CNES), Christophe LATRY (CNES), Dominique LEGER (ONERA), Françoise VIALLEFONT (ONERA)

IV.1. Introduction

 IV.2. Image spot and MTF

    IV.2.1. Review of the theory of stationary linear systems

    IV.2.2. Imagers

    IV.2.3. Expression of the image spot and MTF

    IV.2.4. Overall model

 IV.3. Sampling

    IV.3.1. The effects of sampling

    IV.3.2. Impact on system design

 IV.4. Image interpolation

    IV.4.1. General introduction

    IV.4.2. Classical interpolation

    IV.4.3. 1-D interpolating filters

    IV.4.4. 2D interpolating filters

    IV.4.5. Interpolation in the Fourier domain

 IV.5. Treatments for improving resolution

    IV.5.1. Introduction

    IV.5.2. Deconvolution

    IV.5.3. Denoising

    IV.5.4. Panchromatic/multispectral Fusion

 IV.6. In-flight methods of measuring MTF and focusing errors

    IV.6.1. Introduction

    IV.6.2. Methods for measuring focus error

    IV.6.3. Methods for measuring MTF

    IV.6.4. Conclusion

 IV.7. Conclusion

IV.8. Annexe 1: The Fourier transform

    IV.8.1. The continuous Fourier transform

    IV.8.2. Going from the continuous to the discrete world: sampling

    IV.8.3. A suitable tool for the sampled world: the Discrete Fourier transform

    IV.8.4. The finite discrete Fourier transform

IV.8.5. Summary: from continuous Fourier transform to finite discrete

Fourier transform

    IV.8.6. FDFT properties

    IV.8.7. Use of the FDFT

    IV.8.8. Conclusion

 IV.9. Annexe 2: wavelets and packets

    IV.9.1. Limitations of the frequency representation

    IV.9.2. Wavelets

 IV.10. Annexe 3: Interpolation and B-splines

    IV.10.1. Basic properties of interpolating functions

    IV.10.2. Spline construction

 IV.11. Bibliography

V. SYSTEM DIMENSIONING

Philippe KUBIK (CNES)

V.1. Objective and definitions

 V.2. Dimensioning principles

    V.2.1. Geometry

    V.2.2. Radiometry

    V.2.3. Resolution

 V.3. Design examples

    V.3.1. SPOT type mission, 10 m

    V.3.2. Satellite with metre-scale resolution

 V.4. Conclusions

VI. IMAGE COMPRESSION

Catherine LAMBERT (CNES), Christophe LATRY (CNES), Gilles MOURY (CNES)

VI.1. Introduction

 VI.2. General overview of image compression

 VI.3. Compression and image quality

    VI.3.1. Inadequacy of the usual criteria

    VI.3.2. Consideration of the overall onboard/ground image system

    VI.3.3. User application criteria

 VI.4. Diversity of compression techniques in the space field

    VI.4.1. Predictive coding techniques

    VI.4.2. DCT encoding techniques

    VI.4.3. Lapped Orthogonal Transform (LOT).

    VI.4.4. Wavelet transform compression

    VI.4.5. Future prospects

    VI.4.6. Bibliography

VII. IMAGE SIMULATION

Philippe LIER (CNES), Christophe VALORGE (CNES)

 VII.1. The purpose of image simulation

    VII.1.1. Review: the concept of 'Image Quality’

    VII.1.2. Simulation: a design tool

    VII.1.3. Simulation: an interface tool

 VII.2. General principles of image simulation

    VII.2.1. Simulating the input scene either for the sensor, or for

    pre-processing

    VII.2.2. Simulating the sensor

    VII.2.3. Simulating the ground processing

    VII.2.4. Summary

    VII.2.5. Examples of how this processing system is used at CNES

    VII.2.6. The limitations of 'traditional’ simulation

    VII.2.7. Comments

 VII.3. Image synthesis and 3D simulation

    VII.3.1. Reminder: modelling scenes in '2.5D’

    VII.3.2. Modelling scenes in 3D

    VII.3.3. Pre-processing in 3D

    VII.3.4. 3D simulation

 VII.4. Outlook for image simulation

VIII. CONCLUSION

Philippe LIER (CNES)

VIII.1. The resolution race

VIII.2. Other criteria

    VIII.2.1. The revisit interval

    VIII.2.2. The spectral bands

    VIII.2.3. Stereoscopic imagery

    VIII.2.4. Operational capability

 VIII.3. High resolution imagery for everyday use?