In real water environments， common imaging problems include contrast reduction， low definition， and information attenuation. The traditional estimation method involves estimating the polarization information of the entire image. In real underwater images， the target has complex polarization characteristics， the restoration effects of some target areas are poor， and even degradation occurs. In this study， a method of polarization parameter partition optimization restoration for water-degraded images was proposed. First， the connected domain of an object with high and low polarizations was extracted after two images were processed with orthogonal polarization by block contrast enhancement and guided filtering. Based on the pixel values in the polarization image， the extraction process of high and low polarization object regions was optimized. Second， the polarization of each object was estimated， which solved the problem of incorrect estimation of complex objects in traditional global estimation methods. Finally， the image of polarization degree of backscattered light was iteratively optimized to obtain the optimal selection. Experimental results show that the subjective visual quality of the image is improved significantly. In two initial experiments， the original light intensity maps under low turbidity are compared. The measurement of enhancement by entropy （EME） value of the objective evaluation index and the contrast increases by 554% and 528% on average， respectively. In a third set of experiments， in which a comparison of the original light intensity maps in an environment of low illumination and high turbidity was conducted， the EME value and contrast are improved by 379% and 956%， respectively. Three sets of natural image quality evaluation （NIQE） indices indicate the proposed method has good performance， and a more natural image is produced. Compared with the traditional method， the proposed method can effectively restore a turbid image， increase image contrast， weaken information attenuation， and achieve a better image sharpening effect.