Ultrasound (US) imaging is an indispensable tool for diagnostic imaging, particularly given its cost, safety, and portability profiles compared to other modalities. However, US is challenged in subjects with morphological heterogeneity (e.g., those with overweight or obesity), largely because conventional imaging algorithms do not account for such variation in the beamforming process. Specific knowledge of the these spatial variations enables supplemental corrections of these algorithms, but with added computational complexity. Wavefield correlation imaging (WCI) enables efficient image formation in the spatial frequency domain that, in its canonical formulation, assumes a uniform medium. In this work, we present an extension of WCI to arbitrary known speed-of-sound distributions directly in the image formation process, and demonstrate its feasibility in silico, in vitro, and in vivo. We report resolution improvements of over 30% and contrast improvements of order 10% over conventional WCI imaging. Together our results suggest heterogeneous WCI (HWCI) may have high translational potential to improve the objective quality, and thus clinical utility, of ultrasound images.