Electrowetting display is a new reflective display which depends on ambient light display. It has the advantages of low power consumption, no radiation, fast response speed and easy colorization. It has a broad application prospect in electronic paper industry. However, in practical application, there are some problems in electrowetting electronic paper, such as ink reflux, oil film rupture, charge capture, contact angle hysteresis and so on. When electrowetting electronic paper displays images, there will be some problems, such as unclear image detail texture, image distortion and low contrast, which affect the display of electrowetting electronic paper. In view of the display characteristics and existing problems of the electrowetting display, in order to highlight the image of the target area more effectively and improve the contrast of the image, an image enhancement algorithm of electrowetting display based on image segmentation and dynamic histogram equalization is proposed. This algorithm combines the advantages of Otsu and maximum entropy segmentation algorithm, and proposes Otsu and maximum entropy threshold segmentation algorithm based on variance weight. Firstly, using this segmentation algorithm, the image is divided into background area and target area. Secondly, the original image histogram is divided into four sub histograms by taking the brightness mean value of the two regions and the selected threshold based on variance weight as the segmentation points, and then the sub histograms are reassigned. Finally, the four sub histograms are equalized. The advantage of this algorithm is to separate the target area and background area of the image and carry out targeted enhancement processing. While maintaining the average brightness of the target area and background area of the image, it improves the contrast of the image and highlights the target area of the image, so as to enrich the details of the image and make the whole image three-dimensional and full. The algorithm is simulated on MATLAB platform. Experimental results indicate that compared with other HE algorithms which partition the histogram, the image quality evaluation index PSNR is improved by 25.6%~45.5%, the entropy difference ΔE is reduced by 29.1%, and SSIM is closer to 1. At the same time, when it is applied to the electrowetting display, the image has higher contrast, the content of the image becomes richer and has better visual effect.