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The low definition of ground object boundaries in unmanned aerial vehicle visible light remote sensing images can easily lead to a decrease in the differentiation between ground object targets and the background, making it difficult to extract ground object targets. To this end, a method for extracting ground objects from unmanned aerial vehicle visible light remote sensing images is proposed. Analyze the features of unmanned aerial vehicle visible light remote sensing images from three aspects: spectral features, texture features, and edge features. Augmenting the unmanned aerial vehicle visible light remote sensing image dataset by combining three image features. Define image encoding labels for the expanded dataset to determine the weight of ground object enhancement. By parameterizing the spectral features of ground object targets, calculate the spectral absorption index, and obtain the expression for ground object extraction, the unmanned aerial vehicle visible light remote sensing image ground object extraction can be achieved. The experimental results show that the proposed method can ensure the clarity of the boundary of ground objects and has strong ability to extract ground objects.