Microscope image denoising algorithm based on wavelet transform

When capturing images from the microscope imaging system, the images captured are blur and the information in the images is lost due to noise interference in the collection process. The process of microscopy imaging and the algorithm of microscope image denoising based on wavelet transform are discussed in this paper. Spectrum value and noise variance are used to evaluate the denoising effect. The best value of the wavelet transform number and the range of wavelet transform threshold parameter are obtained after many experiments. The experiments results show that the algorithm can be used without knowing any priori knowledge of the image, and it doesn't depend on the image's size to judge the de-nosing threshold and even doesn't need the image's noise variance information. The denoising effect using this method is better than using other traditional algorithms such as neighborhood average, median filter and low-pass filter.