1. A system for image registration utilizing particle swarm optimization, the system comprising one or more processors that are configured to perform operations of: selecting a set of image windows from a test image; transforming each image window from the test image, such that a transformation of each image window aligns each image window with a reference image having a center, resulting in a set of transformed image windows; configuring a plurality of software agents to operate as a cooperative swarm to optimize an objective function, wherein each agent is assigned an initial velocity vector to explore a multi-dimensional solution space, where each agent is configured to perform at least one iteration, the iteration being a search in the multi-dimensional solution space for a potential objective function where each agent keeps track of a first position vector representing a current individual best solution that the agent has identified, and a second position vector used to store the current global best solution among all agents; evaluating an objective function at the location of each agent, wherein the objective function represents a measure of registration quality between the set of transformed image windows and the reference image; and comparing the current global best solution found by all of the agents with an optimum solution, wherein if the global best solution is within a predetermined threshold of the optimum solution, then the global best solution represents the registration; and wherein the objective function is defined as: J = ( 1 N ⁢ ∑ k = 1 N ⁢ λ k ⁡ ( I max - d _ k ) , where N denotes the number of image windows, Σ represents a summation, λ k denotes the fraction of overlap of a kth image window with the reference image, I max is the maximum pixel value of the test image, and d k denotes the average absolute difference between the image window and the reference image.