Normalization is a canonical nonlinear computation that underlies multisensory integration, attention, and other sensory processing. In this computation, the response of one neuron to a set of stimuli is normalized by the weight of all the presented stimuli – not just its preferred stimulus. Normalization is ubiquitous and conserved across species, suggesting its fundamental role in brain processing. When central brain computations go awry, the consequences can be severe – and normalization has been implicated in brain disorders like autism. While normalization has been described in multiple modalities and species, its functional circuitry and mechanism remain unknown. This project aims to produce an experimental model to address that gap. Specifically, here, we investigate divisive normalization in awake mouse visual cortex. This mouse model will enable the use of powerful in vivo genetic, electrophysiology, imaging, optogenetic, and psychophysics techniques.Using transgenic mice, excitatory neurons in mouse V1 were functionally labelled with GCaMP6s. Two-photon imaging was used to capture the activity of large V1 excitatory populations in awake mice presented with cross-inhibitory stimuli designed to evoke normalization. We recorded from hundreds of tuned and untuned neurons in an unbiased manner and observed tuned normalization similar to what has been observed in other species. These findings were cross-validated using electrophysiological recordings. Additionally, in our electrophysiology data, normalization strength was observed to have a depth dependence, suggesting the need for further study of laminar differences in this computation. Our data suggest that normalization can be visually evoked and measured in the V1 of awake, head-fixed mice, opening the door to further functional and mechanistic study. Furthermore, we examined how normalization influences population pairwise noise correlations. We observed that normalization increased the correlation of similarly orientation-selective pairs with high normalization strength and decreased the correlation of oppositely orientation-selective pairs with high normalization strength. We also observed that in mice, in contrast with macaques, normalization decreased the correlation of similarly orientation-selective pairs with low normalization strength. Normalization mechanisms underlie the changes in pairwise correlations that can explain improved behavioral performance in attention, so further understanding of normalization will help better understand processes that modify pairwise correlations, like attention. We anticipate that this work will provide groundwork for continuing to study normalization in the mouse and may ultimately lead to circuit dissection and behavioral assays, contributing to an understanding of the role of normalization in normal physiology and behavior, aberrant circuitry, and disease.