In this paper, techniques to improve the overall efficiency of an image encoding algorithm that is specifically designed to be used in Wireless Sensor Networks (WSN) are proposed. The inherent nature of WSN, which contains numerous network nodes each having its computational resources, makes the algorithm is being underutilized due to its sequential nature and hence there is a scope to improve speedup by applying the concepts of parallelization on it. The other avenues which are pertinent to the task are the usage of GPU for computation of large arrays as well as the concept of cluster computing to run the algorithm on a cluster of nodes. Another point of importance for such an algorithm is the utilization of memory and how to make its usage more efficient. Hence, the concept of pre-allocation is also applied to the algorithm to make it run faster. An in-depth study of the algorithm is conducted by considering various parameters such as the size and complexity of the key, histogram analysis, correlation values, etc. © 2021 IEEE.