Application of Image Denoising Algorithm and Data Mining in Psychological Teaching Quality Evaluation

Abstract

In order to improve the psychological teaching quality of college students, this paper combines image denoising algorithm and data mining algorithm to construct a psychological teaching quality evaluation system. The denoising algorithm is mainly used to identify the behavior and expressions of the students so as to explore the psychological state of the students. Moreover, this paper combines the data mining algorithm to carry out the quantitative analysis of students’ psychological state and analyzes and introduces the calibration principle of Dirckx method in detail to improve it and then forms a new calibration method. In addition, based on the arctangent function, this paper proposes a new two-frame random phase-shift fringe image phase shift extraction algorithm. The research results show that the image denoising algorithm and data mining proposed in this paper have a good effect in the evaluation method of psychological teaching quality and can play a good role in the improvement of students’ mental health.