Histogram computation based on image bitwise decomposition

In this paper, a new method to compute the image histogram is presented, along with the image maximum and minimum values. It is intended for highly parallel architectures such as the ones found in focal plane processors (FPP). This new approach exploits this parallelism relying on the privatization technique to avoid the memory collision problem, while the bin frequency is obtained through image bitwise manipulation. Unlike traditional privatization techniques, our method exhibits a trade-off between processing time and bin size. That is, it can be adapted as a power-of-two bin size histogram and the computation time decreases exponentially as the bin size is reduced on each power of two, allowing high computational flexibility.