Unimap Home Page
Unimap is a map maker for the PACS and SPIRE instruments, which are the infrared imaging photometers onboard the ESA Herschel satellite. Unimap produces high quality images from the raw (level 1) instruments data.
Unimap is developed by the DIET dept. of the University of Rome 'La Sapienza', in cooperation with the ASDC center of the Italian Space Agency (ASI), the IAPS Institute of the National Astrophysic Institute (INAF) and the European Space Astronomy Centre (ESAC) of the European Space Agency (ESA).
The following funding is gratefully acknowledged:
> 2011-2012. ASI. In the framework of the Hi-Gal project.
> 2012-2014. Sapienza University. In the framework of the Unimap project.
> 2015-2016. ESA. In the framework of the Unido project.
Unimap is a light mapper, producing high quality images with a modest hardware. To give an idea, an input dataset of 400 Msamples can be processed on a laptop with 8 Giga RAM, with a processing time that depends on the data and may vary from 1 to 5 hours.
Unimap is easy to use. It is automatic, in the sense that good images are normally obtained with the default settings. The quality may sometime be improved by tuning the parameters.
Unimap is written in Matlab and runs wherever Matlab can be installed. However it does not need Matlab to run. Compiled versions are currently available for Mac and Linux (64 bit machines).
Click here for more details on the processing chain, documentation and Users' Manual.
History and status
The development started in sept. 2011, partially funded by the ASI. Unimap was designed to be the successor of Roma-GAL , which is the map maker developed within the Hi-GAL project. In particular the goal was to obtain a simple, automatic and easy to distribute software, keeping the Roma-GAL image quality.
The development proceeded in 2012, funded by the University of Rome. In the light of the Map-Making Workshop held at ESAC in january 2013, Unimap was optimised with the goal of improving performance and flexibilty.
The image quality was satisfactory and stable since version 5.0 (sept. 2012). The quality was evaluated at the Map-Making Workshop using several metrics.
From 2014 to 2015, the software has been optimized for speed and the automatic settings of the processing parameters improved (version 6.2.0).
In 2015 and 2016, within the UNIDO project, funded by the ESAC, the image quality has been further improved, by compensating for the pointing error and pixel noise. The noise map has been added.
In 2017, the software has been frozen, following a final debugging and parameter tuning activity.
The last version of Unimap is 7.1.0 (Linux and Mac).
> Code development and algorithm design: Lorenzo Piazzo.
> Interface development: Luca Calzoletti, Fabiana Faustini, David Ikhenaode, Michele Pestalozzi.
> Testing and performance verification: Bruno Altieri, Michele Pestalozzi, Stefano Pezzuto, Davide Elia, Eugenio Schisano, Fabiana Faustini, Luca Calzoletti, Lorenzo Piazzo.
> Compilation and distribution: David Ikhenaode, Luca de Nardis, Alessandro Falaschi.
1) You cannot redistribute Unimap.
2) You cannot make any commercial or profit use of Unimap.
3) If you publish images obtained with Unimap, give credits, by citing , , , ,  and .
Concerning the last point note that Unimap was obtained by improving the pipeline of . The whole processing chain is described in . The PGLS/WGLS algorithm is described in . The drift removal is described in [3,5]. The pointing error compensation is described in . The pixel noise correction is described in .
Also, please let us know that you downloaded Unimap by writing an email to firstname.lastname@example.org
The Unimap source code of Unimap 5.5.0 is released under a BSD Open Source License an can be downloaded by clicking here.
Maintenance and development
Bugs affecting the latest Unimap release are fixed as soon as possible. For bug reporting, write an email to email@example.com. Please setup an FTP site with the inupt files (unimap_obsid_*) and the parameters and log files (unimap_par.txt and unimap_log.txt) causing the problem.
There are several planned improvements (e.g. RPE correction, PACS coaddition compensation) that will be implemented as time permits. Suggestions and comments from the users are appreciated. It is possible to get improvements and extensions (e.g. to non Herschel data) by funding Unimap in the framework of a research contract with the DIET dept.
Creating Unimap input data
Unimap does not directly interface with HIPE and has its own data format. Input data suitable for Unimap can be produced on any machine where HIPE is installed by means of a tool developed by the ASDC, named UniHIPE. The tool can be downloaded, together with the documentation, from the ASDC site, by clicking here. UniHIPE is also available as a HIPE plug-in. Moreover, since HIPE 13 a script for running Unimap is included in the PACS library.
For troubles with Unimap, write an email to firstname.lastname@example.org.
 A. Traficante, L. Calzoletti, M. Veneziani, B. Ali, G. de Gasperis, A.M. Di Giorgio, F. Faustini, D. Ikhenaode, S. Molinari, P. Natoli, M. Pestalozzi, S. Pezzuto, F. Piacentini, L. Piazzo, G. Polenta, E. Schisano: ''Data reduction pipeline for the Hi-GAL survey'', Monthly Notices of the Royal Astronomical Society, Volume 416, Issue 4, Pages 2932-2943, October 2011.
 L. Piazzo, D. Ikhenaode, P. Natoli, M. Pestalozzi , F. Piacentini and A. Traficante: "Artifact removal for GLS map makers by means of post-processing", IEEE Trans. on Image Processing, Vol. 21, Issue 8, pp. 3687-3696, 2012.
Compact citation: Piazzo, L., Ikhenaode, D., Natoli, P., et al. 2012, ITIP, 21, 3687.
 L. Piazzo, P. Panuzzo, M. Pestalozzi: "Drift removal by means of alternating least squares with application to Herschel data", Signal Processing, vol. 108, pp. 430-439, 2015.
 L. Piazzo, L. Calzoletti, F. Faustini, M. Pestalozzi, S. Pezzuto, D. Elia, A. di Giorgio and S. Molinari: 'Unimap: a Generalised Least Squares Map Maker for Herschel Data', MNRAS, 2015, 447, pp. 1471-1483.
 L. Piazzo, M. C. Raguso, J. G. Carpio and B. Altieri: "Least Squares Image Estimation in the Presence of Drift and Pixel Noise", European Signal Processing Conference (EUSIPCO), Budapest, Hungary, August 2016.
 L. Piazzo, M. C. Raguso, L. Calzoletti, R. Seu, B. Altieri: "Least Squares Time-Series Synchronization in Image Acquisition Systems", IEEE Trans. on Image Processing, Vol, 25, Issue 9, pp. 4458-4468, September 2016.
 L. Piazzo: 'Least Squares Image Estimation for Large Data in the Presence of Noise and Irregular Sampling', submitted to the IEEE Trans. on Image Processing, copy available by the author, 2017.
Last update: June 16th, 2017.