Painting Psychotherapy Image Measurement and Reconstruction Algorithm based on Improved Hadamard Matrix

Abstract

Painting psychotherapy based on Internet technology has become a method of mental health testing and treatment. This method will produce a large number of digital images of painting psychotherapy. How to measure and reconstruct the image is the basis of automatic analysis and processing. This study aimed to propose a painting psychotherapy image measurement and reconstruction algorithm based on the improved Hadamard matrix. Moreover, the construction of a measurement matrix was analyzed using the compressed sensing theory and the Hadamard matrix construction algorithm was improved and optimized. Also, four different measurement matrices were compared and analyzed. The findings revealed that the improved Hadamard measurement matrix achieved good experimental results in terms of signal reconstruction accuracy and Peak Signal-to-Noise Ratio (PSNR) value. In the experimental analysis of painting psychotherapy image reconstruction, the reconstruction algorithm based on the improved Hadamard measurement matrix had a shorter reconstruction time and the algorithm achieved satisfactory results in terms of the number of iterations and the PSNR value of the reconstructed image. For painting psychotherapy images, the algorithm provided a theoretical basis for later digital processing, large-sample training and analysis and automatic machine recognition and judgment.