Recent years have seen increased attention being given to measure Heart Rate with remote-PPG. Previous work mainly focused on optimal signal extraction from three channels of a webcam. Several robust signal extraction methods using either optic models or frequency analysis have been discussed before. After applied these algorithms, residual noise still emerges occasionally with short time duration and relative high energy. This paper investigates the cause of residual noise and then proposed an algorithm based on continuous wavelet transform (CWT) to reduce the highly dynamic residual noise. With noise reduction and signal reconstruction, the advantages of both CWT and FFT are integrated to cope with the motion/illuminance induced residual noise. The results obtained by this system show improved SNR ratio and Entropy under both motion and stationary conditions.