ing at the problem that nonuniform cloud is difficult to remove effectively by using single algorithms for high resolution remote sensing satellite images, an optimization algorithm based on image segmentation and improved dark channel prior method is proposed. The original cloud image is segmented into a dense fog area and a thinner fog area by the image segmentation technique. The dense fog area adopts weighted multiscale Retinex algorithm to realize local enhancement and remove the fog. The thinner fog area adopts the improved dark color method, transforming the dark color image defogging model from RGB color space to HSI color space, extracting the luminance component, and obtaining accurate atmospheric optical values. The atmospheric transmittance is optimized by the tolerance mechanism, and the defogged image is obtained by enhancement of the automatic gradation method. Experimental results show that the proposed algorithm can restore image details and recover image color and clarity effectively.