Edge regularized restoration for laser bubble detection

Abstract

Laser bubble detection based on optical photography is widely used in industrial areas such as air tightness measurements. However, the precision of detection is severely affected by the degradation of detecting images. In order to enhance the visual quality of bubble detection, an image semiblind restoration method with edge regularization is applied along with the estimation of the dynamic modulation transfer function. We use objective-image quality metrics to limit the deconvolution iterations of the semiblind deconvolution algorithm. We compare the performance of the binary morphology filter. Improvement by the proposed method can be seen from the experimental results. It can be concluded that the proposed approach can effectively enhance quality and edge details of the laser bubble detecting images, so that greater precision can be achieved.