Background: Assessing the extent of ischemic and reperfusion-associated myocardial injuries remains challenging with current magnetic resonance imaging (MRI) techniques. Our aim was to develop a tissue characterization mapping (TCM) technique by combining late gadolinium enhancement (LGE) with our novel percent edema mapping (PEM) approach to enable the classification of tissue represented by MRI voxels as healthy, myocardial edema (ME), necrosis, myocardial hemorrhage (MH), or scar. Methods: Six dogs underwent closed-chest myocardial infarct (MI) generation. Serial MRI scans were performed post-MI on days 3, 4, 6, 14, and 56, including T2 mapping and LGE. Dogs were sacrificed on day 4 (n = 4, acute MI) or day 56 (n = 2, chronic MI). TCMs were generated based on a voxel classification algorithm taking into account signal intensity from LGE and T2-based estimation of ME. TCM-based MI and MH were validated with post mortem triphenyl tetrazolium chloride (TTC) staining. Pearson’s correlation and Bland-Altman analyses were performed. Results: The MI, ME, and MH measured by TCM were 13.4% [25th–75th percentile 1.6–28.8], 28.1% [2.1–37.5] and 4.3% [1.0–11.3], respectively. TCM measured higher MH and MI compared to TTC (p = 0.0033 and p = 0.0007, respectively). MH size was linearly correlated with MI size by both MRI (r = 0.9528, p < 0.0001) and TTC (r = 0.9625, p < 0.0001). MH quantification demonstrated good agreement between TCM and TTC (r = 0.8766, p < 0.0001, 2.4% overestimation by TCM). A similar correlation was observed for MI size (r = 0.9429, p < 0.0001, 6.1% overestimation by TCM). Conclusions: Preliminary results suggest that the TCM method is feasible for the in vivo localization and quantification of various MI-related tissue components.