Fast autofocusing of recorded planes by salient feature region for coherent diffraction imaging

In multi-distance coherent diffraction imaging, the task of distance calculation for multi-diffraction images is cumbersome. The information features are hard-to-extract and the region of interest extraction algorithms are difficult to be adopted. A universal salient feature region selection algorithm by using the area with the highest density of corners is proposed to extract the most representative feature region. In addition, equally spaced recording modes and mismatched diffraction distances will result in system noise and destroy image quality. The polydirectional maximum gradient is offered as a sharpness criterion to weigh a quantitative feature for the final pattern. A fast, sensitive, and high-accuracy autofocusing and sample reconstruction can be achieved using only a small number of images while ensuring that morphological properties and quantification of the reconstructions are not compromised. The proposed method is promising for biological and medical dynamic observations for computational imaging systems. Feature region extraction method based on Harris corner detection is proposed to reduce the computational load during the sharpness evaluation and avoid the influence of background on location results. The variable interval recording mode is designed to speed up the recording of diffraction patterns and image reconstruction to improve imaging quality. Polydirectional maximum gradient-based clarity criteria promote sensitive and accurate positioning.image