国产欧美精品一区二区,中文字幕专区在线亚洲,国产精品美女网站在线观看,艾秋果冻传媒2021精品,在线免费一区二区,久久久久久青草大香综合精品,日韩美aaa特级毛片,欧美成人精品午夜免费影视

Aerial remote sensing images have the characteristics of small target size and rich information content. However, due to the interference of low rank noise, this leads to a decrease in the accuracy of extracting small targets and an increase in missed detections. To address this issue, a small target extraction method for aerial remote sensing images based on singular value decomposition is proposed. According to the singular value decomposition criterion, combined with the non-uniform variation of singular value eigenvectors, small targets are extracted and the energy gain of singular value transformation is calculated. Construct a covariance matrix of signal spatial clutter under this constraint, reflecting the distribution of signals and the connections between different signals. Using singular value decomposition matrix to avoid the impact of calculating clutter covariance matrix, reflecting the shape, size, texture and other information of small targets in the image. Singular value decomposition image matrix, reflecting the strength information of rows, columns, and pixels in the image. Decompose the orthogonal matrix and reconstruct the image matrix by selecting a new set of basis vectors. Compress the image and divide it into three parts: scattered targets, fully stacked targets, and partially stacked targets. Calculate the energy attenuation factor of these three parts to complete the extraction of small targets in aerial remote sensing images. According to the experimental results, the recall and accuracy of this technology are high, and the maximum number of missed small targets on the ship is 4, indicating that the use of this technology has a precise and efficient extraction effect.