  One of the fundamental goals of modern Astronomy is to estimate the physical
parameters of galaxies from images in different spectral bands. We present a
hierarchical Bayesian model for obtaining age maps from images in the \Ha\ line
(taken with Taurus Tunable Filter (TTF)), ultraviolet band (far UV or FUV, from
GALEX) and infrared bands (24, 70 and 160 microns ($\mu$m), from Spitzer). As
shown in S\'anchez-Gil et al. (2011), we present the burst ages for young
stellar populations in the nearby and nearly face on galaxy M74.
  As it is shown in the previous work, the \Ha\ to FUV flux ratio gives a good
relative indicator of very recent star formation history (SFH). As a nascent
star-forming region evolves, the \Ha\ line emission declines earlier than the
UV continuum, leading to a decrease in the \Ha\/FUV ratio. Through a specific
star-forming galaxy model (Starburst 99, SB99), we can obtain the corresponding
theoretical ratio \Ha\ / FUV to compare with our observed flux ratios, and thus
to estimate the ages of the observed regions.
  Due to the nature of the problem, it is necessary to propose a model of high
complexity to take into account the mean uncertainties, and the
interrelationship between parameters when the \Ha\ / FUV flux ratio mentioned
above is obtained. To address the complexity of the model, we propose a
Bayesian hierarchical model, where a joint probability distribution is defined
to determine the parameters (age, metallicity, IMF), from the observed data, in
this case the observed flux ratios \Ha\ / FUV. The joint distribution of the
parameters is described through an i.i.d. (independent and identically
distributed random variables), generated through MCMC (Markov Chain Monte
Carlo) techniques.
