For the current channel attention mechanism used for super-resolution reconstruction, there are problems that the attention prediction destroys the direct corresponding relationship between each channel and its weight and the mechanism only considers the first-order or second-order channel attention without comprehensive consideration of the advantage complementation. Therefore, a mixed-order channel attention network for image super-resolution reconstruction was proposed. First of all, by using the local cross-channel interaction strategy, increase and reduction in channel dimension used by the first-order and second-order channel attention models were changed into a fast one-dimensional convolution with kernel k, which not only makes the channel attention prediction more direct and accurate but makes the resulting model simpler than before. Besides, the improved first and second-order channel attention models above were adopted to comprehensively take the advantages of channel attentions of different orders, thus improving network discrimination. Experimental results on the benchmark datasets show that compared with the existing super-resolution algorithms, the proposed method has the best recovered texture details and high frequency information of the reconstructed images and the Perceptual Indictor (PI) on Set5 and BSD100 datasets are increased by 0.3 and 0.1 on average respectively. It shows that this network is more accurate in predicting channel attention and comprehensively uses channel attentions of different orders, so as to improve the performance.

The teaching of Chinese architecture history has building structures too complex, is limited to 2D planar teaching and is not easy for students to master and apply, therefore an implementation method of Chinese architecture history teaching system based on mixed reality technology was proposed. The wooden structure system of Baoguo Temple in Ningbo was taken as an example, and the mixed reality device Microsoft HoloLens was used as the teaching platform. Firstly, 3ds Max was applied to the 3D simulation modeling of the wooden structure system of Baoguo Temple based on the collected data, and a building model library was built. Then, the 3D human-computer interface of the virtual teaching system was constructed in unity3D, the key technologies were used including environment understanding and human-computer interaction based on C# scripts, and a Chinese architectural history teaching system using HoloLens was implemented with core functions of building structure recognition and cultural cognition. The results show that the system has good 3D visual effects and natural effective human-computer interaction, which can improve the efficiency of knowledge transfer and the initiative of students.