We propose a definition of a Sharpness Index that is closely related to the notion of Global Phase Coherence recently introduced for automatic image restoration and image quality assessment. Using Gaussian random fields instead of random phase images, we can estimate the probability that a random image has a given Total Variation, which leads us to an explicit formula and a fast algorithm. Theoretical arguments and numerical experiments are given to assess the similarity between the Sharpness Index and the Global Phase Coherence, and an application to non-parametric blind deconvolution is presented, that illustrates the possibilities offered by this new approach.

The Fourier phase spectrum of an image is well known to contain crucial information about the image geometry, in particular its contours. In this paper, we show that it is also strongly related to the image quality, in particular its sharpness. We propose a way to define the Global Phase Coherence (GPC) of an image, by comparing the likelihood of the image to the likelihood of all possible images sharing the same Fourier power spectrum. The likelihood is measured with the total variation (Rudin-Osher-Fatemi implicit prior), and the numerical estimation is realized by a Monte-Carlo simulation. We show that the obtained GPC measure decreases with blur, noise, and ringing, and thus provides a new interesting sharpness indicator, that can be used for parametric blind deconvolution, as demonstrated by experiments.

Most satellites decouple the acquisition of a panchromatic image at high spatial resolution from the acquisition of a multispectral image at lower spatial resolution. Pansharpening is a fusion technique used to increase the spatial resolution of the multispectral data while simultaneously preserving its spectral information. In this paper, we consider pansharpening as an optimization problem minimizing a cost function with a nonlocal regularization term. The energy functional which is to be minimized decouples for each band, thus permitting the application to misregistered spectral components. This requirement is achieved by dropping the, commonly used, assumption that relates the spectral and panchromatic modalities by a linear transformation. Instead, a new constraint that preserves the radiometric ratio between the panchromatic and each spectral component is introduced. An exhaustive performance comparison of the proposed fusion method with several classical and state-of-the-art pansharpening techniques illustrates its superiority in preserving spatial details, reducing color distortions, and avoiding the creation of aliasing artifacts.

ABSTRACT:The Pleiades system, ORFEO system optical component (Optical and Radar Federated Earth Observation) consists of a constellation of two satellites for very High Resolution panchromatic and multispectral optical observation of the Earth. Its mission is to cover all European civilian needs (mapping, tracking floods and fires) and defence in the category of metric resolution: 0.7m Nadir. The first Pleiades satellite was launched at the end of last year. One of the key objectives of the Pleiades HR (PHR) project is to achieve a location accuracy that will allow the use of images in GIS (Geographical Information System) without geometrical model improvement by refining on ground control points. The image location without refined model was specified with the precision of the most commonly used tool ie the civil GPS. So the location accuracy has been specified at less than 12m for 90% of the images on a nominal satellite configuration. Very special care has been taken all along the PHR project realization to achieve this very good location accuracy. The final touch is given during the in-orbit commissioning phase which lasts until June 2012. The geometric quality implies to tune the parameters involved in the geolocation model (geometric calibration): besides attitude and orbit restitution tuning (not considered here), it consists in estimating the biases between the instrument orientation and the AOCS reference frame, and also the sight line of each detector in the focal plane. This is called static geometrical model. The analysis of dynamic perturbations outside of the model are the second most important image quality objective of in-flight commissioning, not described in this paper. Finally "image quality assessment" consists in evaluating the image quality obtained in the final products. For geolocation model, it is quantified by the absolute geolocation and the pointing accuracies, and it is a main contributor in length alteration and planimetric and altimetric accuracies. In this paper we will present both the different practices we have adopted (their advantages, limitations and complementarities) and the means we are using for the operational assessment of the location quality of PHR images. We will focus on the innovative methods and mention the improvements in progress. To conclude, we will present the very first accuracy results assessed after PHR1A launch on L1 and Sensor products.

ABSTRACT:The first Pleiades-HR satellite, part of a constellation of two, has been launched on December 17, 2011. This satellite produces high resolution optical images. In order to achieve good image quality, Pleiades-HR should first undergo an important 6 month commissioning phase period. This phase consists in calibrating and assessing the radiometric and geometric image quality to offer the best images to end users. This new satellite has benefited from technology improvements in various fields which make it stand out from other Earth observation satellites. In particular, its best-in-class agility performance enables new calibration and assessment techniques. This paper is dedicated to presenting these innovative techniques that have been tested for the first time for the Pleiades-HR radiometric commissioning. Radiometric activities concern compression, absolute calibration, detector normalization, and refocusing operations, MTF (Modulation Transfer Function) assessment, signal-to-noise ratio (SNR) estimation, and tuning of the ground processing parameters. The radiometric performances of each activity are summarized in this paper.