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Coral reef substrate classification plays a crucial role in marine resource development and marine ecological protection. At present, deep learning semantic segmentation methods are widely used in the field of remote sensing image classification, but less research has been conducted in substrate classification. Due to the high cost of pixel-by-pixel labeling in the fully supervised deep learning-based method, it is not suitable for large-scale and high-frequency substrate classification work. The semi-supervised deep learning-based method can effectively use the labeled labels to generate pseudo-labels for unlabeled data, thus effectively reducing the labor cost, however, the performance of the existing semi-supervised method is vulnerable to the interference of pseudo-label noise. To address the above problems, this paper proposes a semi-supervised substrate classification method based on soft and hard collaborative decision making. First, a high quality Pseudo tag is generated using joint decision making of multiple models; then, a loss function (Collaboration Choice of decision Confidence Loss function, 3CLoss) is proposed to take into account the confidence of Pseudo tag pixels and guide the model for training; finally, a soft and hard collaborative decision making approach is used to obtain accurate substrate classification results. The accuracy of this paper was evaluated on the shallow benthic habitat atlas datasets of Buck Island Reef in the northern part of St. Croix, U.S. Virgin Islands, and Pearl and Hermes Atolls, about 400 km southeast of Midway Island, Hawaiian Islands, and the experimental results show that the accuracy of the proposed method is comparable to that of the fully supervised learning method, and 3.08% higher than that of the mainstream semantic segmentation methods on average, which can effectively serve the coral reef substrate survey.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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