Image Processing and Data Analysis

Starck, Jean-Luc; Murtagh, Fionn; Bijaoui, A.

doi:10.1017/cbo9780511564352

Cited by 496 publications

(265 citation statements)

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“…1.5.1 of Starck et al (1998), multiresolution tools based on a wavelet transform suffer from several problems, in particular they create negative artefacts around the sources. In addition, since the emission is smoothed with the scaling function (Φ) to produce the large-scale planes, the shape of the large-scale structures is not preserved and tends toward the shape of Φ (which, in turn, creates the negative artefacts in the small-scale planes mentioned above).…”

Section: Appendix B: Assumptionsmentioning

confidence: 99%

The end of star formation in Chamaeleon I?

Беллоче

Schüller

Parise

et al. 2011

A&A

144

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Context. Chamaeleon I is the most active region in terms of star formation in the Chamaeleon molecular cloud complex. Although it is one of the nearest low-mass star forming regions, its population of prestellar and protostellar cores is not known and a controversy exists concerning its history of star formation. Aims. Our goal is to search for prestellar and protostellar cores and characterize the earliest stages of star formation in this cloud. Methods. We used the bolometer array LABOCA at the APEX telescope to map the cloud in dust continuum emission at 870 μm with a high sensitivity. This deep, unbiased survey was performed based on an extinction map derived from 2MASS data. The 870 μm map is compared with the extinction map and C 18 O observations, and decomposed with a multiresolution algorithm. The extracted sources are analysed by carefully taking into account the spatial filtering inherent in the data reduction process. A search for associations with young stellar objects is performed using Spitzer data and the SIMBAD database. Results. Most of the detected 870 μm emission is distributed in five filaments. We identify 59 starless cores, one candidate first hydrostatic core, and 21 sources associated with more evolved young stellar objects. The estimated 90% completeness limit of our survey is 0.22 M for the starless cores. The latter are only found above a visual extinction threshold of 5 mag. They are less dense than those detected in other nearby molecular clouds by a factor of a few on average, maybe because of the better sensitivity of our survey. The core mass distribution is consistent with the IMF at the high-mass end but is overpopulated at the low-mass end. In addition, at most 17% of the cores have a mass larger than the critical Bonnor-Ebert mass. Both results suggest that a large fraction of the starless cores may not be prestellar in nature. Based on the census of prestellar cores, Class 0 protostars, and more evolved young stellar objects, we conclude that the star formation rate has decreased with time in this cloud. Conclusions. The low fraction of candidate prestellar cores among the population of starless cores, the small number of Class 0 protostars, the high global star formation efficiency, the decrease of the star formation rate with time, and the low mass per unit length of the detected filaments all suggest that we may be witnessing the end of the star formation process in Chamaeleon I.

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Section: Appendix B: Assumptionsmentioning

confidence: 99%

The end of star formation in Chamaeleon I?

Беллоче

Schüller

Parise

et al. 2011

A&A

144

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“…In order to count the hybridization dots on confocal Z-series, we used the METAMORPH software (Molecular Devices, http://www.moleculardevices.com/) and particularly the multidimensional image analysis (MIA) module developed by Racine et al (2007). The method is based on locally adaptive noise filtering and 2-D segmentation by wavelet transformation (Starck et al, 1998) followed by maximal projection of the segmented images. The number of dots was estimated on this projection by measuring the surface of the segmented objects and taking into account the area of a standard object previously defined from multiple 2-D images.…”

Section: Image Analysismentioning

confidence: 99%

In planta quantification of endoreduplication using fluorescent in situ hybridization (FISH)

et al. 2011

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SUMMARYEndopolyploidy, i.e. amplification of the genome in the absence of mitosis, occurs in many plant species and happens along with organ and cell differentiation. Deciphering the functional roles of endopolyploidy is hampered by the fact that polyploid tissues generally comprise cells with various ploidy levels. In some fleshy fruits (amongst them tomato fruit) the ploidy levels present at the end of development range from 2C to 256C in the same tissue. To investigate the temporal and spatial distribution of endopolyploidy it is necessary to address the DNA content of individual nuclei in situ. Conventional methods such as fluorometry or densitometry can be used for some tissues displaying favorable characteristics, e.g. small cells, small nuclei, organization in a monolayer, but high levels of varying polyploidy are usually associated with large sizes of nuclei and cells, in a complex three dimensional (3-D) organization of the tissues. The conventional methods are inadequate for such tissue, becoming semi-quantitative and imprecise. We report here the development of a new method based on fluorescent in situ bacterial artificial chromosome hybridizations that allows the in situ determination of the DNA ploidy level of individual nuclei. This method relies on the counting of hybridization signals and not on intensity measurements and is expected to provide an alternative method for mapping endopolyploidy patterns in mature, 3-D organized plant tissues as illustrated by the analysis of ploidy level and cell size in pericarp from mature green tomato fruit.

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“…Let us have a data set D (particles in simulations or luminosity weighted galaxies in SDSS data), located in a box of size n×n×n. The wavelet transform decomposes the data set as a superposition of the form (A.9) where c J is the smoothed version of the original data D, and w j represents the structure of D at scale 2 j (see Starck et al 1998;Starck & Murtagh 2002). The wavelet decomposition output is J three-dimensional density fields D j and wavelets w j of size n × n × n. Following the traditional indexing convention, we denote density fields and wavelets of the finest scale as j = 1.…”

Section: A3 Waveletsmentioning

confidence: 99%

Wavelet analysis of the cosmic web formation

Einasto

Hütsi

Saar

et al. 2011

A&A

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Context. According to the modern cosmological paradigm, galaxies and galaxy systems form from tiny density perturbations generated during the very early phase of the evolution of the Universe. Aims. Using numerical simulations, we study the evolution of the density perturbation phases of different scales to understand the formation and evolution of the cosmic web. Methods. We apply the wavelet analysis to follow the evolution of high-density regions (clusters and superclusters) of the cosmic web. Results. We show that the maxima and minima positions of density waves (their spatial phases) almost do not change during the evolution of the structure. Positions of density perturbation extrema of are more stable for large scale perturbations. In the context of the present study we call density waves of scale ≥64 h −1 Mpc large, waves of scale 32 h −1 Mpc medium, and waves of scale 8 h −1 Mpc small, within a factor of 2. Conclusions. In the cosmic structure formation of the synchronisation (coupling) of density waves of different scales plays an important role.

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Image Processing and Data Analysis

Cited by 496 publications

References 0 publications

The end of star formation in Chamaeleon I?

The end of star formation in Chamaeleon I?

In planta quantification of endoreduplication using fluorescent in situ hybridization (FISH)

Wavelet analysis of the cosmic web formation

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