Digital twin technology can support teachers in this major to complete monitoring related topics and application research and serve teaching and scientific research through the establishment of automatic monitoring teaching model laboratory and in-depth combination with the current students’ skill training needs in this major. This exploration aims to make the visual sensor industry have a steady stream of talents. Promoting the development of visual sensor technology is to promote the development of science and technology. Based on the teaching research of visual sensing design using digital technology, a set of teaching systems of visual sensing design is designed by using the methods of literature research and investigation and analysis. Special topics are set up from the aspects of professional subjects; regarding course content, various sensor principle research courses, visual sensor design courses, experimental courses, and example courses are set up; teaching methods are divided into online and offline synchronous classes; the evaluation method should focus on the distribution, examples, and practice. The results show that traditional classroom teaching is seriously separated from extracurricular learning. Most students are in a state of passive acceptance of knowledge and have few thinking activities. The established teaching system integrates brain and cognition, photoelectric foundation, sensory imaging, visual sensing imaging, visual sensing technology courses, computer technology, virtual experiment courses, and physical experiment courses. It can carry out more than 30 experiments of optical microscopic imaging and X-ray imaging based on the principle of visual sensing. Therefore, the teaching effect and teaching mode of the proposed digital visual sensing teaching system have been greatly improved.

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In order to study the application of computer digital image processing technology in film and television (FAT) animation visual sensing expression, by studying the principle of digital image processing technology and visual sensing technology, a spatial image adaptive steganography image enhancement algorithm by multiscale filters is proposed to carry out enhancement processing of the original image in FAT production. This algorithm can provide more high-quality and refined original materials for FAT animation production, which is convenient for FAT animation postproduction to produce higher-resolution and clear FAT works. Finally, the algorithm is verified. The results show that the spatial image adaptive steganography image enhancement algorithm has high security, and the highest average detection error rate is 25.06%. When α = 0.4 , the security of the spatial image adaptive steganography image enhancement algorithm is up to 34.62% and the image distortion rate is low. The established image enhancement algorithm can significantly improve the security of the existing spatial image steganography algorithm under different embedding rates, especially at a high embedding rate; the improvement of the spatial domain steganography algorithm is greater. The proposed steganographic image enhancement algorithm by image preprocessing has higher security and better image enhancement effect.

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