Unimap Download Page

By downloading Unimap, you accept the following terms of use:

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 [2], [3], [4], [5], [6] and [7].

Concerning the last point note that Unimap was obtained by improving the pipeline of [1] and by adding the PGLS/WGLS algorithm, which is described in [2] and is perhaps the main novelty introduced, and the ALS algorithm, described in [3]. A paper covering the whole software is [4].

Also, please let us know that you downloaded Unimap by writing an email to lorenzo.piazzo@uniroma1.it

[1] 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.

[2] 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.

[3] 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.

[4] 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.

[5] 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.

[6] 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.

[7] 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.


Below you find the latest Unimap releases. Click here for older versions.

Click here to download Unimap release 7.1.0 for Linux 64 bit.

Click here to download Unimap release 7.1.0 for Mac 64 bit.

In order to use Unimap, you need to install the MCR (Matlab Compiler Runtime) first. If you already installed the correct MCR, you do not need to redo it, just use the old one. If you do not have the MCR installed, you should download the MCR from the Mathworks site and install it: For the Linux version, from rel. 6.0.0, select the MCR for Matlab 2014b, Linux64bit, v8.4. For the Mac version, from rel. 6.3.3, select the MCR for Matlab 2015b, Mac64bit, v9.0.