Image contrast enhancement is crucial in image processing. Traditional methods often struggle with low-contrast images. A new method based on clustering was proposed. The number of clusters in the histogram is determined from the original image. Histogram components are classified using the K-means algorithm. By comparing cluster ranges and pixel rates, histogram stretching and equalization are selectively applied. Experimental results show that this new method is more effective than traditional techniques.