Sysiphe is an airborne hyperspectral imaging system, result of a cooperation between France (Onera and DGA) and
Norway (NEO and FFI). It is a unique system by its spatial sampling -0.5m with a 500m swath at a ground height of
2000m- combined with its wide spectral coverage -from 0.4μm to 11.5μm in the atmospheric transmission bands. Its
infrared component, named Sieleters, consists in two high étendue imaging static Fourier transform spectrometers, one
for the midwave infrared and one for the longwave infrared. These two imaging spectrometers have very close design,
since both are made of a Michelson interferometer, a refractive imaging system, and a large IRFPA (1016x440 pixels).
Moreover, both are cryogenic and mounted on their own stabilization platform which allows at once to actively control
and independently measure the line of sigh. These data are useful to reconstruct and to georeference the spectral image
from the raw interferometric images. Sysiphe first flight occurred in September, 2013.
When illuminated by a plane wave, continuously self-imaging gratings (CSIGs) produce a field whose intensity
profile is a propagation- and wavelength-invariant biperiodic array of bright spots. In the case of an extended
and incoherent source, we show that CSIGs produce multiple images of the source. The fundamental properties
of these gratings will be derived. In particular, methods to assess the image quality in angle of CSIGs will be
introduced. It turns out that this new type of pinhole-array camera works on the same principle as diffractive
axicons, which are known to produce wavelength-invariant nondiffracting beams. The formalism developed for
CSIGs will be also extended to axicons. CSIGs and axicons both produce focal lines and can be robust in field, in
compensation of a trade-off with the resolution. They also offer interesting properties in terms of compactness,
achromaticity and long depth of focus for imaging systems. However, compared to classical imaging systems,
they produce degraded images and an image processing is necessary to restore these images. Experimental images
obtained with these components in the visible and infrared spectral ranges will be presented.
We present a quality criterion for telescopes based on the fulfillment of observation needs as defined by a client. It is intended for the pre-conception and broad control level. The criterion is built from the fidelity measure by limiting the spatial scales taken into account to the scales useful to the proper imaging of the detail of interest. By construction this mono-dimensional criterion allows trade-off between spatial and radiometric resolution. The comparison of different design strategies is also possible, for example between undersampled large aperture telescopes and well sampled smaller telescopes. It can also be used to predict the usefulness of each available telescope for a given observational purpose. Being global, the criterion requires only high-level specifications, thus allowing the client to exercise a greater degree of control over the instrument definition. We present here a pre-calibration of the mission quality criteria enabling to give an absolute quality value for the telescope and to determine whether the observation mission is fulfilled. A comparison of test-case telescopes is then made by varying several design parameters.
Proc. SPIE. 4829, 19th Congress of the International Commission for Optics: Optics for the Quality of Life
KEYWORDS: Image compression, Calibration, Image processing, Digital filtering, Linear filtering, Quality measurement, Quantization, Image filtering, Human vision and color perception, Nonlinear filtering
Numerous methods of contrast compression create artefacts or unnatural looking image. For best information gathering, we propose here to combine two different processes: an efficient edge extraction and an histogram adjustment process.
Proc. SPIE. 4372, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XII
KEYWORDS: Signal to noise ratio, Visual process modeling, Imaging systems, Image processing, Image analysis, Image quality, Signal processing, Visual system, Modulation transfer functions, Systems modeling
To ensure that an imaging system supplies images that meet the needs of the observation mission, it is important to assess the imaging system performance. In this paper we propose a new quality criterion for imaging system assessment. This method is based on three parts: end-to-end analysis of the imaging system, standardized expression of the mission by an objective definition of the observation tasks and 'a priori' knowledge of the properties of the objects to be observed. This quality criterion can also be used as a tool to aid in the design of observation systems based on the properties of the objects to be observed.
An optimal imaging system must fulfill its specifications without an expensive and undue quality. However the translation of high-level human requirements into low-level system demands is not easy. As human specifications deal only with objects or scenes to be sen, the knowledge of these objects and its properties relevant to the information transfer through the imaging system is critical. As many imaging system quality criteria are based on the knowledge of second order statistical properties of scenes or objects to be imaged, the goal of this paper is to show that it is possible to extract these properties from high-level mission requirements.
The Modulation Transfer Function (MTF) is of fundamental importance in the testing of imaging systems as it is used to characterize the transfer of the spatial frequencies for the observed object. Different techniques based on the use of periodic targets made of unresolved lines or points have been proposed to assess this figure of merit for sampled imaging systems. The main potential problem in implementation of these methods is the fact that it is often difficult to insure a good balance in intensity between the individual lines or points belonging to the target. In a recent paper, we describe an analytical model allowing a first estimation of the importance of this problem. The purpose of this paper is to present this model and to apply it to the specific case of the 2D characterization of the MTF of an imaging system.