Research on saliency detection algorithm of rural homestead

Xing Chen; Wanghu Li II; Jing Gao III; Deyao Zeng IV; Bo Wen V

doi:10.1117/12.2636770

6 May 2022 Research on saliency detection algorithm of rural homestead

Xing Chen, Wanghu Li II, Jing Gao III, Deyao Zeng IV, Bo Wen V

Proceedings Volume 12176, International Conference on Algorithms, Microchips and Network Applications; 121760Z (2022) https://doi.org/10.1117/12.2636770
Event: International Conference on Algorithms, Microchips, and Network Applications 2022, 2022, Zhuhai, China

Abstract

Uav remote sensing images have the characteristics of complex background and multiple noise interference. If significance detection is carried out before rural homestead identification, the target rural homestead can be located quickly and accurately, providing location information for the detection of rural homestead, thus improving the detection efficiency of rural homestead. In this paper, we studied four commonly used algorithms of FT, HC, LC and AC with good saliency detection effect. The experimental results show that the detection time of LC algorithm is at least 0.63 ms, and the longest time of FT algorithm is 24.46 ms. The LC algorithm is more suitable for the saliency detection of rural homestead images in this paper.

Citation Download Citation

Xing Chen, Wanghu Li II, Jing Gao III, Deyao Zeng IV, and Bo Wen V "Research on saliency detection algorithm of rural homestead", Proc. SPIE 12176, International Conference on Algorithms, Microchips and Network Applications, 121760Z (6 May 2022); https://doi.org/10.1117/12.2636770

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KEYWORDS

Detection and tracking algorithms

Fourier transforms

Target detection

Unmanned aerial vehicles

Remote sensing

Distance measurement

Image processing

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