Contextual Contrast Limited Adaptive Histogram Equalization (C-CLAHE) is an effective method for solving the noise amplification effect of the adaptive histogram equalization (AHE), and enhancing the visibility of local details of an image. Even though C-CLAHE has a smaller memory foot print than CLAHE, complexity of the interpolation process increases the computation demand dramatically. Therefore, FPGA based implementations have been limited to CLAHE only. In this study three key modifications were introduced to the CCLAHE, and for the first time make it feasible to implement on a resource limited FPGA. Here restructured the method so that the histogram redistribution stage is realized with fewer number of iterations. Then implemented contrast limitation calculations earlier during the histogram generation stage instead of during the histogram redistribution stage, which reduces the block RAM demand and finally mathematically derive an alternative interpolation calculation u