Interference Stripe Noise Reduction of CMOS Sensor-Based Digital Holographic Measurement System

Abstract

Comparing with the application of charge coupled device (CCD) sensor, a kind of interference stripe noise (ISN) can be observed easily from the complementary metal-oxide-semiconductor (CMOS) sensor-based digital holographic measurement (DHM) system because a series of optic coatings and filters are used in front of that sensor in order to improve its imaging effect. The improper assembly or the micro manufacturing error of these optic components may create the unexpected interference phenomena in the imaging sensor. To reduce that noise, an effective image processing method is developed. On one hand the Laplacian pyramid method is used to highlight the ISN and a cartoon-texture decomposition technique is carried out to remove the additive ISN. On the other hand, an improved Lee filtering is performed to restrain the multiplicative ISN. Extensive experiment results have shown that the image quality can be improved after the ISN reduction and this method is fit for solving a deionized water temperature estimation application where the texture complexity of target image is relatively low.

Reflection Coefficient Estimation of Femtosecond Laser Surface Processing Using Support Vector Regression

“…Second, after laser processing, the ablation diameters of femtosecond laser are measured by typical SEM images. The image features of Gray-Level Co-occurrence Matrix (GLCM) [13] are also computed for SEM images. Third, a Support Vector Regression (SVR) [14] is trained by the laser process parameters and GLCM image features above for the laser ablation diameter prediction.…”