Adaptive iterative guided filtering for suppressing background noise in ptychographical imaging

In many industrial applications, military technology, and biomedical fields, coherent diffraction imaging technology has gradually replaced classical camera imaging methods. Coherent diffraction imaging extends the Ptychographic Iterative Engine (PIE) technique, which provides a large field of view in addition to high-resolution imaging. However, in the actual imaging process, there are many kinds of noise with different intensities and distributions in the reconstructed image due to the mechanism of PIE and imaging equipment. These noises will not only slow down the imaging speed and reduce the imaging quality, but also lead to the failure of direct image reconstruction. In this paper, an adaptive iterative guided filtering algorithm is proposed based on PIE reconstruction characteristics. By introducing a filter control factor into the PIE reconstruction algorithm, the intensity of the filter will gradually increase with PIE iteration. The edge-preserving property of the guided filter can protect the details well. According to the TOG evaluation function, compared with unfiltered PIE reconstruction, the method increased by 0.625, and the image quality improved by 50%. Compared with other image filtering functions, the TOG of reconstructed images increased by 20%. In terms of operation efficiency, this method increases the operation time by less than 10%, and its efficiency is higher than other filtering algorithms under the same iteration times.