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 paral- lel architectures such as the ones found in Focal Plane Processors (FPP). This new approach exploits this par- allelism 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-o 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 exibility.