an image processing system comprising a processor configured to:

receive a two-dimensional image of a scene from a camera system and a point cloud of the scene having a first resolution from a light detection and ranging system;

create transformed points by mapping point locations for a portion of points in the point cloud describing a three-dimensional representation of the scene to corresponding pixel locations in the two-dimensional image of the scene to form the transformed points;

create a fused data array using the two-dimensional image and the transformed points, wherein each transformed point corresponds to a pixel in the two-dimensional image and to a matched element in a number of matched elements in the fused data array;

calculate a goodness score using a combination of a distance of a transformed point mapped to a pixel corresponding to the matched element from the camera system, a dissimilarity of the matched element to other matched elements wherein the goodness score increases as the dissimilarity increases, and a depth value in a data vector associated with the matched element, wherein the goodness score is generated based on a relationship where:

 and

Δ_i=d_i ^o·γ,

wherein:

G _i is the goodness score of an i^th matched element;

M_i is a dissimilarity score for the i^th matched element;

Δ_i is a distance measurement for the i^th matched element;

j is an index for an n matched elements;

F is a response to a feature;

m is a number of features;

d_i^o is the depth value in a data vector associated with the i^th matched element; and

γ is a normalizing constant;

use the goodness score to identify a number of support elements; use the fused data array and the number of support elements to identify new points for the point cloud;

add the new points to the point cloud to form a new point cloud, wherein the new point cloud has a second resolution greater than the first resolution; and

identify the object in the scene using the new point cloud.