A novel wavelet denoising method used for droplet volume detection in the microfluidic system

Microdroplet is found increasing use in the production of nanoparticles, chemical reactions and drug research and development. However, only some simple theory of droplet information is studied, automate droplet is the direction in the future. Size of droplet is detected in order to control the flow of the microfluid in automation droplet system. Image collected by image acquisition system has severe noise and denoising is the most important step. This paper describes a new wavelet threshold function to improve the wavelet threshold denoising. This approach successfully denoises the noise in the image. Compared with traditional wavelet threshold denoising, this approach has enormous improvements in objective evaluation of denoising such as Peak Signal Noise Ration (PSNR). With the demand of constant accurate flow in microfluidic system, the approach to measure droplet is in urgent need. The obtained results are in good agreement with the demand. The method is used to detect the radius of droplets in the microfluidic system. If dust or spot images are directly processed with noisy bring out error result even not able to be detected. Better results are achieved after processed by the approach in this paper. That boots application of microfluidic system in field of pharmacy, microchemistry, biochemistry and bioanalysis.