In order to detect the Cd stress levels of rice growing in natural environment fast and accurately, based on wavelet transform technology in the visible light and near-infrared region (NIR), a method of identifying stress levels of rice under Cd pollution was explored. The hyperspectral data, biochemical parameters and heavy metals concentration in folium were collected for the rice growing in natural farmlands. Wavelet transform of hyperspectral reflectance (350～1 300 nm) was performed by using Daubechies 5 mother function and wavelet energy coefficients of spectral reflectance were extracted. In addition, the model between wavelet energy coefficient and Cd content was established. The result showed that the wavelet coefficients of the fifth decomposition level (d5) proved successful for detecting Cd pollution of rice; the singularity range of rice located in the region around 550~810 nm of spectral signal under Cd pollution; and the singularity amplitude was 0.04; The centre of modulus maxima located at 700 nm. Regression model based on third level wavelet energy coefficient can estimate the Cd content of rice accurately with the coefficient of determination (R2) of 0.958, and root mean square error (RMSE) of 0.122. It can be concluded that the singularity analysis technology applying wavelet transform to reflectance has been shown to be very promising in detecting rice under Cd pollution effectively, and wavelet energy coefficients can estimate Cd content of rice, and provide important reference for detecting other metal-induced stress on crop.