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This paper takes the rice plot as the research object, and uses the portable UAV Mavic Pro for aerial photography. Preprocess the acquired UAV images to generate orthophotos with a resolution of 3.95cm/pix. Using object-oriented thinking, visual evaluation and ESP tools are combined to quickly select the optimal segmentation scale to be 300, and support is applied. Vector machine, random forest, and nearest neighbor supervised classification methods have carried out ground object classification and rapid extraction of rice area. The classification results and area accuracy are evaluated by visual classification results. The method with the highest overall accuracy is the nearest neighbor classification method. At this time, the user accuracy of rice classification is 95%, and the area consistency accuracy is 99%. The results show that UAV remote sensing and automatic classification can quickly obtain high resolution images and extract rice planting area in plain rice planting area, make up for the lack of ground survey data when Nongshan is blocked, and provide samples and verification basis for the calculation of large-scale rice planting area, yield and other information.Povzetek: Predstavljen je sistem za analizo UAV posnetkov za iskanje površin riža.

With the rapid iteration of computer digital tech, the processing level of remote sensing image has made outstanding achievements and progress, which greatly improves the processing level and ability of remote sensing image. Therefore, the research on remote sensing image processing assisted by computer digital tech has important practical value. Based on this, this paper first analyzes the digital characteristics and properties of remote sensing image, then studies the remote sensing image processing process based on computer digital tech, and finally gives the development trend of remote sensing image processing based on computer digital tech.

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