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Noise reduction from two frame speckle-shifting ghost images with morphology algorithms

ABSTRACT Edge detection is the basis of image segmentation and object recognition, as edge generally contains important information of an object. In this paper, we propose a novel speckle-shifting ghost imaging (SSGI) method to extract the edge of an unknown object. In this method, the gradient operation is directly carried out to the illumination patterns rather than the captured object image. The structured patterns for illumination are only divided into two groups, which can extract the edge in all directions. The imaging result is clearer than the conventional SSGI, but the noise is still serious. To solve the problem, we further investigate a denoising method with morphology algorithms, such as frame difference and connected region labelling. Numerical simulations and experiments are carried out to verify the feasibility and effectiveness.