Sonar image is seriously polluted by noise, which leads to the problem of low precision in underwater multi-target segmentation.?Therefore，this paper proposes an underwater multi-object segmentation technique based on self-adjusting spectrum clustering，combined with the entropy weight method.?The technology firstly clusters through self-tuning spectral clustering of sonar image pixel clustering processing, so that the image is divided into multiple independent areas. According to the complementarity and redundancy of multiple features, the information entropy, brightness, contrast and narrow length of each region are calculated. The entropy weight method is used to weight multiple features and select the optimal target region. Then，the optimal target region is matched with all regions by multi-feature similarity. Finally, all target regions are segmented automatically by the adaptive threshold iterative method according to the matching results of similarity. Experimental results show that there is no over-segmented of noise interference regions, and target regions segmented have higher accuracy, which verifies the effectiveness of the proposed method.