Impulsive noise removal from color images with morphological filtering

This paper deals with impulse noise removal from color images. The proposed noise removal algorithm employs a novel approach with morphological filtering for color image denoising; that is, detection of corrupted pixels and removal of the detected noise by means of morphological filtering. With the help of computer simulation we show that the proposed algorithm can effectively remove impulse noise. The performance of the proposed algorithm is compared in terms of image restoration metrics and processing speed with that of common successful algorithms.Comment: The 6th international conference on analysis of images, social networks, and texts (AIST 2017), 27-29 July, 2017, Moscow, Russi

Restoration of hyperspectral astronomical data with spectrally varying blur

International audienceIn this paper we present a method for hyper-spectral image restoration for integral field spectrographs (IFS) data. We specifically address two topics: (i) the design of a fast approximation of spectrally varying operators and (ii) the comparison between two kind of regularization functions: quadratic and spatial sparsity functions. We illustrate this method with simulations coming from the Multi Unit Spectroscopic Explorer (MUSE) instrument. It shows the clear increase of the spatial resolution provided by our method as well as its denoising capability

Restoration of hyperspectral astronomical data from Integral field spectrograph

International audienceIn this paper we present a method for hyper-spectral image restoration for integral field spectrographs (IFS) data. It takes advantage of all the spectral and spatial correlations in the observed scene to enhance the spatial resolution. We illustrate this method with simulations coming from the Multi Unit Spectroscopic Explorer (MUSE) instrument. It shows the clear increase of the spatial resolution provided by our method as well as its denoising capability

Apodization in high-contrast long-slit spectroscopy. Closer, deeper, fainter, cooler

The spectroscopy of faint planetary-mass companions to nearby stars is one of the main challenges that new-generation high-contrast spectro-imagers are going to face. In a previous work we presented a long slit coronagraph (LSC), for which the presence of a slit in the coronagraphic focal plane induces a complex distribution of energy in the Lyot pupil-plane that cannot be easily masked with a binary Lyot stop. To alleviate this concern, we propose to use a pupil apodization to suppress diffraction, creating an apodized long slit coronagraph (ALSC). After describing how the apodization is optimized, we demonstrate its advantages with respect to the CLC in the context of SPHERE/IRDIS long slit spectroscopy (LSS) mode at low-resolution with a 0.12" slit and 0.18" coronagraphic mask. We perform different sets of simulations with and without aberrations, and with and without a slit to demonstrate that the apodization is a more appropriate concept for LSS, at the expense of a significantly reduced throughput (37%) compared to the LSC. Then we perform detailed end-to-end simulations of the LSC and the ALSC that include realistic levels of aberrations to obtain datasets representing 1h of integration time on stars of spectral types A0 to M0 located at 10 pc. We insert spectra of planetary companions at different effective temperatures (Teff) and surface gravities (log g) into the data at angular separations of 0.3" to 1.5" and with contrast ratios from 6 to 18 mag. Using the SD method to subtract the speckles, we show that the ALSC brings a gain in sensitivity of up to 3 mag at 0.3" with respect to the LSC, which leads to a much better spectral extraction below 0.5". In terms of Teff, we demonstrate that at small angular separations the limit with the ALSC is always lower by at least 100K, inducing an increase of sensitivity of a factor up to 1.8 in objects' masses at young ages. [Abridged]Comment: 15 pages, 17 figures. Accepted for publication in A&

Restoration of Hyperspectral Astronomical Data with Spectrally Varying Blur

This book is a collection of 19 articles which reflect the courses given at the Collège de France/Summer school “Reconstruction d'images − Applications astrophysiques“ held in Nice and Fréjus, France, from June 18 to 22, 2012. The articles presented in this volume address emerging concepts and methods that are useful in the complex process of improving our knowledge of the celestial objects, including Earth

Resolving stellar populations with crowded field 3D spectroscopy

(Abridged) We describe a new method to extract spectra of stars from observations of crowded stellar fields with integral field spectroscopy (IFS). Our approach extends the well-established concept of crowded field photometry in images into the domain of 3-dimensional spectroscopic datacubes. The main features of our algorithm are: (1) We assume that a high-fidelity input source catalogue already exists and that it is not needed to perform sophisticated source detection in the IFS data. (2) Source positions and properties of the point spread function (PSF) vary smoothly between spectral layers of the datacube, and these variations can be described by simple fitting functions. (3) The shape of the PSF can be adequately described by an analytical function. Even without isolated PSF calibrator stars we can therefore estimate the PSF by a model fit to the full ensemble of stars visible within the field of view. (4) By using sparse matrices to describe the sources, the problem of extracting the spectra of many stars simultaneously becomes computationally tractable. We present extensive performance and validation tests of our algorithm using realistic simulated datacubes that closely reproduce actual IFS observations of the central regions of Galactic globular clusters. We investigate the quality of the extracted spectra under the effects of crowding. The main effect of blending between two nearby stars is a decrease in the S/N in their spectra. The effect increases with the crowding in the field in a way that the maximum number of stars with useful spectra is always ~0.2 per spatial resolution element. This balance breaks down when exceeding a total source density of ~1 significantly detected star per resolution element. We close with an outlook by applying our method to a simulated globular cluster observation with the upcoming MUSE instrument at the ESO-VLT.Comment: accepted for publication in A&A, 19 pages, 19 figure

Fragmentation and Connectivity of Island Forests in Agricultural Mediterranean Environments: A Comparative Study between the Guadalquivir Valley (Spain) and the Apulia Region (Italy)

Habitat loss and fragmentation are considered some the main threats to biodiversity. Original forests have suffered an accentuated fragmentation and agricultural homogenization, leaving only some areas of natural vegetation, relegated to strongly anthropized disconnected patches (island forests, IFs) in a hostile matrix. These patches of original vegetation could be the key for the design and management of ecological corridors to promote species migration, an essential strategy for meeting the consequences of Global Change. This study proposes a comparative analysis of the fragmentation and connectivity of IFs of Quercus in two typically Mediterranean areas of predominantly agricultural use: the Guadalquivir valley (Spain) and the Apulia region (Italy). A retrospective comparison is also carried out in the Guadalquivir valley. The aim is to develop an objective new methodology to locate the patches of most interest using quantitative and qualitative data. Reference cartography of current island forests of Quercus species was developed from several digital sources and validated with orthoimages and field observations. Fragmentation analysis was based on graph structures using the software Conefor 2.6, a reliable tool for assessment of the role of patches in the landscape. Area and distance were used as node and connector values. Dispersion distance was established as 500 m, based on the maximum dispersion of acorns. Results indicate that the Guadalquivir valley has suffered an intensive fragmentation in recent decades. Both the Guadalquivir and Apulia regions host some IFs with the relevant potential to contribute as core habitats in the creation of connections to other natural protected sites. Many residual IFs in the landscape could contribute as stepping stones in the design and management of ecological corridors. Our methodology highlights the value of IFs to develop assessment strategies using homogenized available digital cartography and common criteria for the dispersion distances in graph theory analysis. The application of this new methodology could help in the management of protected sites using highly fragmented areas to allow the species movement through inhospitable landscapes in a unique opportunity to connect the different protected areasThis research was funded by the Council of Economy, Innovation, Science and Employment of the Andalusian Government in the framework of the Project “Modelo espacial de distribución de las quercíneas y otras formaciones forestales de Andalucía: una herramienta para la gestión y la conservación del patrimonio natural” (Code P10-RNM-6013) and by FEDER, Junta de Andalucía— Consejería de Economía y Conocimiento. Proyecto UHU-126283

The GraF instrument for imaging spectroscopy with the adaptive optics

The GraF instrument using a Fabry-Perot interferometer cross-dispersed with a grating was one of the first integral-field and long-slit spectrographs built for and used with an adaptive optics system. We describe its concept, design, optimal observational procedures and the measured performances. The instrument was used in 1997-2001 at the ESO 3.6 m telescope equipped with ADONIS adaptive optics and SHARPII+ camera. The operating spectral range was 1.2 - 2.5 microns. We used the spectral resolution from 500 to 10 000 combined with the angular resolution of 0.1" - 0.2". The quality of GraF data is illustrated by the integral field spectroscopy of the complex 0.9" x 0.9" central region of Eta Car in the 1.7 microns spectral range at the limit of spectral and angular resolutions.Comment: 36 pages, 12 figures, accepted by Ex

Data comparison schemes for Pattern Recognition in Digital Images using Fractals

Pattern recognition in digital images is a common problem with application in remote sensing, electron microscopy, medical imaging, seismic imaging and astrophysics for example. Although this subject has been researched for over twenty years there is still no general solution which can be compared with the human cognitive system in which a pattern can be recognised subject to arbitrary orientation and scale. The application of Artificial Neural Networks can in principle provide a very general solution providing suitable training schemes are implemented. However, this approach raises some major issues in practice. First, the CPU time required to train an ANN for a grey level or colour image can be very large especially if the object has a complex structure with no clear geometrical features such as those that arise in remote sensing applications. Secondly, both the core and file space memory required to represent large images and their associated data tasks leads to a number of problems in which the use of virtual memory is paramount. The primary goal of this research has been to assess methods of image data compression for pattern recognition using a range of different compression methods. In particular, this research has resulted in the design and implementation of a new algorithm for general pattern recognition based on the use of fractal image compression. This approach has for the first time allowed the pattern recognition problem to be solved in a way that is invariant of rotation and scale. It allows both ANNs and correlation to be used subject to appropriate pre-and post-processing techniques for digital image processing on aspect for which a dedicated programmer's work bench has been developed using X-Designer