  We present a data-driven technique to analyze multifrequency images from
upcoming cosmological surveys mapping large sky area. Using full information
from the data at the two-point level, our method can simultaneously constrain
the large-scale structure (LSS), the spectra and redshift distribution of
emitting sources, and the noise in the observed data without any prior
assumptions beyond the homogeneity and isotropy of cosmological perturbations.
In particular, the method does not rely on source detection or photometric or
spectroscopic redshift estimates. Here, we present the formalism and
demonstrate our technique with a mock observation from nine optical and
near-infrared photometric bands. Our method can recover the input signal and
noise without bias, and quantify the uncertainty on the constraints. Our
technique provides a flexible framework to analyze the LSS observation traced
by different types of sources, which has potential for wide application to
current or future cosmological datasets such as SPHEREx, Rubin Observatory,
Euclid, or the Nancy Grace Roman Space Telescope.
