Increasing contrast is one of the vital issues in meteorological image processing, which is crucial for improving image quality and weather condition detection. One of the most common methods for enhancing contrast in digital images is histogram equalization. This method is simple and effective, but it often leads to illogical contrast enhancement and displaying images in an unnatural and poor manner. Furthermore, the average brightness of the images is not properly preserved. In this article, a new method for balancing images while maintaining brightness is introduced. This method modifies the histogram of the original image using fuzzy logic and controls the balancing rate by applying a thresholding process. Initially, the average intensity of gray levels is found, and the histogram is divided into two parts. Then, by finding the average of the two sub-histograms, the histogram is divided into four parts. For dynamic equalization, a new range is defined, and each of the sub-histograms is balanced individually. Finally, a normalization process is applied to the output image to preserve the average brightness. Simulation results show that this new method has significantly improved the quality of black and white meteorological images while maintaining brightness.