Traditional elastic reverse-time migration (RTM) involves P-/S-wave separation for the source and receiver wavefields, followed by applying the zero-lag cross-correlation imaging condition to produce PP and PS images. In anisotropic media, P-/S-wave decomposition requires a higher memory and computational cost than that in isotropic media. In addition, finite acquisition apertures and band-limited source functions result in unsatisfactory resolutions and amplitudes. To mitigate these problems, we present an elastic least-squares imaging method for tilted transversely isotropic media and apply it to land multicomponent and marine pressure data. Unlike traditional RTM, we use the relative perturbations to the product of density and squared axial (compressional/shear) velocities as reflectivity models ($$\Delta \ln{C}_{33}$$ and $$\Delta \ln{C}_{55}$$), and estimate them by solving a linear inverse problem. Numerical experiments illustrate that subsurface reflectors can be well resolved in adjoint images for land multicomponent data, because of the presence of both P- and S-waves in seismograms. Least-squares migration helps to further improve spatial resolution and image amplitudes. Since there are no direct S-waves in marine streamer data, adjoint RTM images of $$\Delta \ln{C}_{55}$$ are mainly resolved with the converted S-waves and are not as good as those in $$\Delta \ln{C}_{33}$$ images. By approximating the Hessian inverse, least-squares migration allows us to take advantage of the weak converted P–S–P-waves and improve the $$\Delta \ln{C}_{55}$$ image quality. Numerical experiments for synthetic and field data demonstrate the feasibility and advantage of the proposed least-squares TTI RTM compared with wave-mode separation-based elastic RTM. In field data experiments, we observe that since there are no strong P–S–P converted waves in streamer pressure records from the marine survey, the reflectors in $$\Delta \ln{C}_{55}$$ image might be mainly imaged from P-waves due to the amplitude versus offset (AVO) effects.