Simon Baillarin

Automatic Registration of Optical Images, a Stake for Future Missions: Application to Ortho-Rectification, Time Series and Mosaic Products

Today, new earth observation missions are designed from satellite to ground segment to best fit the end-user needs while reducing the overall costs and complexity. Furthermore, an efficient use of high resolution image data is only possible if its location is accurate enough. The accuracy of the image location model depends on the knowledge of platform and orbital parameters (instruments calibration, satellite orbit and pointing) and also of the ground elevation (Digital Elevation Model). Good accuracy can be ensured by stringent requirements on onboard equipments (GPS, gyro, ...) but also by appropriate ground processing which is easier and less expensive to setup. This paper describes and evaluates an automatic method to improve location models during ground processing. This method has been implemented and tested at CNES for current and new missions (such as SPOT/FORMOSAT image ortho-rectification, Pleiades-HR images mosaicking or Venmus images time-series generation). These results must be considered for future missions designing.

SPOT5: system overview and image ground segment

SPOT5, the fifth satellite of the SPOT remote sensing satellite family was successfully launched on the 4th of May 2002. SPOT5 is designed to ensure continuity of data acquisition and space image services but also to provide users with advanced products. It flies two identical cameras named HRG (High Resolution Geometry) providing a 2.5 m and a 5 m resolution in a panchromatic mode and a 10 m resolution in a multi-spectral mode, still keeping a 60-km ground field. Stereo application complements SPOT5 mission; the satellite flies a specific High Resolution Stereo Instrument (HRS) made up of two telescopes allowing a 20/spl deg/ fore view and a 20/spl deg/ aft view over a 120-km swath, sampling the landscape every 5 m. To be consistent with this new space segment, the image ground segment has been fully redesigned in order to allow worldwide SPOT family reception and products dissemination. The paper presents the mission, the image ground segment architecture and introduces the SPOT products.

Validation of an automatic image orthorectification processing

Following SPOT5 launch, Spotlmage and French National Geographic Institute (IGN) have decided to design a worldwide accurate database called Reference3D/sup TM/ using data from the High Resolution Stereoscopic SPOT5 instrument (HRS). Spotlmage and IGN have also decided to develop and commercialize a system called ANDORRE to produce orthorectifled images thanks to Reference3D/sup TM/ data. ANDORRE has been designed to take advantage of Reference3D/sup TM/ planimetric and altimetric accuracy to automatically register and rectify any image from SPOT satellites. In this framework, CNES is acting as prime contractor to realize and industrialize the algorithms following a preliminary study undertaken by IGN. This paper focuses on the validation of the geometric performances of the algorithms. A special attention is also paid to the processing time in order to achieve the rectification of a 24000/spl times/24000 image in less than one hour.

Pleiades image quality: from users' needs to products definition

Pleiades is the highest resolution civilian earth observing system ever developed in Europe. This imagery programme is conducted by the French National Space Agency, CNES. It will operate in 2008-2009 two agile satellites designed to provide optical images to civilian and defence users. Images will be simultaneously acquired in Panchromatic (PA) and multispectral (XS) mode, which allows, in Nadir acquisition condition, to deliver 20 km wide, false or natural colored scenes with a 70 cm ground sampling distance after PA+XS fusion. Imaging capabilities have been highly optimized in order to acquire along-track mosaics, stereo pairs and triplets, and multi-targets. To fulfill the operational requirements and ensure quick access to information, ground processing has to automatically perform the radiometrical and geometrical corrections. Since ground processing capabilities have been taken into account very early in the programme development, it has been possible to relax some costly on-board components requirements, in order to achieve a cost effective on-board/ground compromise. Starting from an overview of the system characteristics, this paper deals with the image products definition (raw level, perfect sensor, orthoimage and along-track orthomosaics), and the main processing steps. It shows how each system performance is a result of the satellite performance followed by an appropriate ground processing. Finally, it focuses on the radiometrical performances of final products which are intimately linked to the following processing steps : radiometrical corrections, PA restoration, image resampling and PAN-sharpening.

Automatic cloud detection on high resolution images

Remote sensing optical images are often cloudy and then partially unusable. Thus, cloud detection can optimize the image acquisition loop and the end-user image selection. The current pre-processing of SPOT images includes an automatic cloud and snow detection algorithm based on neural networks and fuzzy logic, which globally provides correct cloud masks but with a perfectible confidence. This process must be improved in order to avoid systematic manual re-notation. For Ple/spl acute/iades high resolution (HR) satellite, CNES experiments an innovative cloud detection method based on correlation and stereoscopic effect (B/H ratio) between images. Thanks to the quasi-simultaneous acquisition of the five spectral bands (panchromatic, red, blue, green and near infrared), this new method can be systematically applied, in addition to a radiometric one. This paper focuses on the new detection algorithm for high resolution images, which includes six main steps: (1) generation of 20 m resolution preview images in both multispectral and panchromatic bands, (2) estimation of the misregistration between panchromatic and multispectral previews using a geometric model, a global DTM and an image matching algorithm, (3) computation of the residual parallax consisting in the difference between prediction model and image matching, (4) cloud detection through high parallax value thresholding (5) radiometric analysis for snow and low altitude clouds detection, (6) masks fusion and confidence status computation. This method, still under assessment over various SPOT5 and Quickbird images, seems to be very promising. The results, presented in the paper, show that the method is efficient even for Quickbird images, in spite of the very low B/H ratio value (0.002) close to Ple/spl acute/iades one.

Automatic and generic mosaicing of satellite images

The CNES (the French Space Agency) has specified and developed a fully automatic mosaicing processing unit, in order to generate satellite image mosaics under operational conditions. This tool, called SIGMA, can automatically put each input image in a common geometry, homogenize the radiometry, and generate orthomosaics using stitching lines.

Remote Sensing Image Ground Segment Interoperability: PLEIADES-HR Case Study

Pleiades-HR is a high-resolution optical Earth observation system developed by CNES, for civilian and military users. The launch of the first Pleiades satellite is scheduled in 2008, the second, 18 months later. The Pleiades-HR program is the French part of the French-Italian ORFEO program which also comprises COSMO-SkyMed, an Italian high-resolution radar system. The Pleiades-HR products will be distributed by Spotlmage and will complete the existing SPOT product line. In such a multi-sensors and multi-users context, CNES has decided to design the new Pleiades-HR ground segment pointing the stress on systems interoperability in order to ease the data access from the end user point of view. After a synthetic presentation of the Pleiades HR ground segment and image products, this paper focuses on PLEIADES HR image product definition and cataloguing services, two major points for the image ground segment interoperability. Among all possible solutions, the image product and catalog services have been defined taking into account the PLEIADES-HR system characteristics, its performance requirements and the international standards (ISO-TC211, OGC, image standards, JPEG2000 ...) use and evolution capabilities. The results presented in the paper are also part of a European initiative of ground segment harmonisation studied in the frame of the HMA project with other European Space Agencies.

Fast and accurate denoising method applied to very high resolution optical remote sensing images

Restoration of Very High Resolution (VHR) optical Remote Sensing Image (RSI) is critical and leads to the problem of removing instrumental noise while keeping integrity of relevant information. Improving denoising in an image processing chain implies increasing image quality and improving performance of all following tasks operated by experts (photo-interpretation, cartography, etc.) or by algorithms (land cover mapping, change detection, 3D reconstruction, etc.). In a context of large industrial VHR image production, the selected denoising method should optimized accuracy and robustness with relevant information and saliency conservation, and rapidity due to the huge amount of data acquired and/or archived. Very recent research in image processing leads to a fast and accurate algorithm called Non Local Bayes (NLB) that we propose to adapt and optimize for VHR RSIs. This method is well suited for mass production thanks to its best trade-off between accuracy and computational complexity compared to other state-of-the-art methods. NLB is based on a simple principle: similar structures in an image have similar noise distribution and thus can be denoised with the same noise estimation. In this paper, we describe in details algorithm operations and performances, and analyze parameter sensibilities on various typical real areas observed in VHR RSIs.

Pleiades-HR image products 5 years after launch

Pleiades-HR is a high resolution remote sensing system developed by the French Space Agency (CNES) for civil and military users. The constellation is composed of two identical satellites PHR1A launched on 2011, December 17th and PHR1B launched one year after, on 2012, December 2nd. More than 600 images can be daily acquired by each satellite in various viewing angles conditions: the satellites are able to target images with viewing angles greater than 47°. Since the launch of the first satellite, major improvements have been integrated in the ground processing to enhance the quality of products and offer new options. Starting from a Pleiades-HR system overview, this paper offers a description of the ground processing and presents an assessment of the different products available now, including image quality performances.