In order to solve the problem of high hardware resources consumption in the CLAHE algorithm, two improvements are made to the algorithm from the perspective of hardware implementation. For the cropping thresholds, a method for determining the universal clipping threshold is proposed.The Figure Of Merits(FOM) is constructed based on Information Entropy and Structural Similarity, and the clipping threshold in hardware implementation is set using the best FOM as the evaluation criterion to balance the contrast and distortion degree of the image enhancement and avoid consuming hardware resources to perform extensive calculations on the image data itself. For the redistribution of pixels exceeding the threshold, an improved superthreshold pixel redistribution method is proposed, which only distributes pixels to grayscale levels that do not exceed the threshold and stops redistribution if they exceed the threshold again. This method reduce the distortion while avoiding hardware costs caused by repeated pixel distribution. On the basis of the improved CLAHE algorithm, the low illumination image enhancement system based on FPGA is completed. The experimental results show that image enhancement processing based on the universal cropping threshold can generally achieve higher FOM, thus having better overall image enhancement effect. Compared with conventional methods, the improved pixel redistribution method can increase the average SSIM of the image by 8.88% at the cost of an average IE loss of 3.28%. The low light image enhancement system can achieve image acquisition and processing of 640×480@60 fps. This design can provide a new reference for the hardware implementation of image enhancement algorithm.