Non-contact Heart Rate (HR) detection can be achieved by remote PhotoPlethysmoGraphy (rPPG), which has attracted more and more attention. However, in practical applications, the rPPG signal is very subtle and easily overwhelmed by noise, which makes it difficult to accurately estimate the HR using existing rPPG-based HR detection methods. In view of the above problems, this paper proposes a non-contact heart rate detection method that enhances rPPG signal and suppresses noise. In this method, the chromaticity information in the normal HR distribution band is first amplified by Euler color amplification technology to avoid the rPPG signal being too small and being overwhelmed by noise; then use face detection and tracking technology to select the appropriate skin of interest Region; then extract the amplified chrominance information in the region of interest, and use the blind source separation method and correlation analysis to separate the rPPG signal; finally, the rPPG signal is time-domain filtered and power spectral density analysis to estimate the HR value. Multiple experiments show that the proposed method has higher HR estimation accuracy than previous methods.