A method, comprising: receiving, by an autonomous vehicle, from an imaging system mounted on the vehicle, an image frame, the image frame depicting a portion of a local area surrounding the vehicle; receiving an initial pose of the autonomous vehicle that is an estimate of an actual pose of the autonomous vehicle; loading a plurality of edgels from map data of a High Definition map of the local area based upon the initial pose; analyzing the image frame to identify a plurality of edge pixels within the image frame; for each respective edgel of a subset of the plurality of edgels: projecting the respective edgel onto the image frame, based upon the initial pose; and determining a correspondence between the projected edgel and an edge pixel of the plurality of edge pixels, based upon a distance between the projected edgel and the edge pixel; determining, based upon the determined correspondences, a transformation that if applied to the subset of edgels reduces an aggregate distance between the subset of edgels and their corresponding edge pixels; applying the determined transformation to the initial pose to determine an updated pose of the autonomous vehicle with respect to the actual pose; and providing signals to the vehicle to navigate the autonomous vehicle based on the updated pose of the autonomous vehicle. wherein determining the correspondence between the projected edgel and the edge pixel of the plurality of edge pixels is further based on a level of similarity between a gradient direction of the projected edgel and a gradient direction of the corresponding edge pixel, wherein the gradient indicates a rate of intensity change of pixels, while the orientation indicates a direction of the intensity change. receiving, by an autonomous vehicle, from an imaging system mounted on the vehicle, an image frame, the image frame depicting a portion of a local area surrounding the vehicle; receiving an initial pose of the autonomous vehicle that is an estimate of an actual pose of the autonomous vehicle; loading a plurality of edgels from map data of a High Definition map of the local area based upon the initial pose; analyzing the image frame to identify a plurality of edge pixels within the image frame; for each respective edgel of a subset of the plurality of edgels: projecting the respective edgel onto the image frame, based upon the initial pose; and determining a correspondence between the projected edgel and an edge pixel of the plurality of edge pixels, based upon a distance between the projected edgel and the edge pixel; projecting the respective edgel onto the image frame, based upon the initial pose; and determining a correspondence between the projected edgel and an edge pixel of the plurality of edge pixels, based upon a distance between the projected edgel and the edge pixel; determining, based upon the determined correspondences, a transformation that if applied to the subset of edgels reduces an aggregate distance between the subset of edgels and their corresponding edge pixels; applying the determined transformation to the initial pose to determine an updated pose of the autonomous vehicle with respect to the actual pose; and providing signals to the vehicle to navigate the autonomous vehicle based on the updated pose of the autonomous vehicle.