Entropy thresholding and its parallel algorithm on the reconfigurable array of processors with wider bus networks

Thresholding is the most commonly used technique in image segmentation. We first propose an efficient sequential algorithm to improve the relative entropy-based thresholding technique. This algorithm combines the concepts of the relative entropy with that of the local entropy and also includes the quadtree hierarchical structure in it. Second, we derive a constant time parallel algorithm to solve this problem on the reconfigurable array of processors with wider bus networks (RAPWBN). The system bus bandwidth determines the capacity of data communication between processors. According to the results as shown by Li and Maresca (1989) and by Maresca and Li (1989), we know that the silicon area used by the switching control mechanism is far less than that used by the processor. Instead of increasing the number of processors, we extend the number of buses to increase the power of a parallel processing system. Such a strategy of utilizing the reconfigurable array of processors with wider bus networks not only has the advantage of saving silicon area but also increases the system power enormously. So, we use the RAPWBN to solve the entropy-based thresholding problem.