A method performed by an electronic device is described. The method includes obtaining a first image from a first camera, the first camera having a first focal length and a first field of view. The method also includes obtaining a second image from a second camera, the second camera having a second focal length and a second field of view disposed within the first field of view. The method further includes aligning at least a portion of the first image and at least a portion of the second image to produce aligned images. The method additionally includes fusing the aligned images based on a diffusion kernel to produce a fused image. The diffusion kernel indicates a threshold level over a gray level range. The method also includes outputting the fused image. The method may be performed for each of a plurality of frames of a video feed.

A method performed by an electronic device is described. The method includes obtaining a first image from a first camera, the first camera having a first focal length and a first field of view. The method also includes obtaining a second image from a second camera, the second camera having a second focal length and a second field of view disposed within the first field of view. The method further includes aligning at least a portion of the first image and at least a portion of the second image to produce aligned images. The method additionally includes fusing the aligned images based on a diffusion kernel to produce a fused image. The diffusion kernel indicates a threshold level over a gray level range. The method also includes outputting the fused image. The method may be performed for each of a plurality of frames of a video feed.

Systems and methods for detecting one or more approaching vehicles include one or more processors and an infrastructure camera operable to capture one or more images of surroundings of an ego vehicle. The surroundings include a ramp, one or more lanes of a freeway, and the one or more approaching vehicles, and the ramp and the lanes share at least one merging point. The one or more processors operable to transform the one or more images of surroundings to a bird's eye view of the surroundings, generate a static segmentation map and one or more dynamic objects in the static segmentation map based on the bird's eye view, predict a lane occupancy of the ramp and the lanes based on range estimation of the ego vehicle and the one or more dynamic objects, and transmit information about the predicted lane occupancy to the ego vehicle.

Systems and methods for detecting one or more approaching vehicles include one or more processors and an infrastructure camera operable to capture one or more images of surroundings of an ego vehicle. The surroundings include a ramp, one or more lanes of a freeway, and the one or more approaching vehicles, and the ramp and the lanes share at least one merging point. The one or more processors operable to transform the one or more images of surroundings to a bird's eye view of the surroundings, generate a static segmentation map and one or more dynamic objects in the static segmentation map based on the bird's eye view, predict a lane occupancy of the ramp and the lanes based on range estimation of the ego vehicle and the one or more dynamic objects, and transmit information about the predicted lane occupancy to the ego vehicle.