A photometric redshift is an estimate for the recession velocity of an astronomical object such as a galaxy or quasar, made without measuring its spectrum.
The photometric redshift technique has come back into mainstream use since 2000, as a result of large sky surveys conducted in the late 1990s and 2000s which have detected a large number of faint high-redshift objects, and telescope time limitations mean that only a small fraction of these can be observed by spectroscopy.
The technique relies upon the spectrum of radiation being emitted by the object having strong features that can be detected by the relatively crude filters.
For example, if a Sun-like spectrum had a redshift of z = 1, it would be brightest in the infrared rather than at the yellow-green color associated with the peak of its blackbody spectrum, and the light intensity will be reduced in the filter by a factor of two (i.e. 1+z) (see K correction for more details on the photometric consequences of redshift).
[4] In recent years, Bayesian statistical methods and artificial neural networks have been used to estimate redshifts from photometric data.