Single-shot X-ray radiograph technology via ultrafast laser can be used to image the internal structure of ultra-high velocity objects with high spatial and temporal resolution, providing a new technical means to observe the internal structure, planarity and other morphological parameters of flyers. However, the wide energy spectrum of high-energy X-rays produced by laser bombardment of the target is accompanied by strong disturbances such as high-energy electrons and scattered rays, which causes great interference to X-ray imaging signal-to-noise ratio and image quality. Besides, the laser pulse width is extremely narrow (picosecond or femtosecond levels) and the data acquisition time of the radiation detector is extremely short, resulting in a low photon count, high quantum statistical noise, and low image signal-to-noise ratio. In addition, the plasma around the flyer makes it more difficult to observe the structure of the flyer, and the image quality is difficult to satisfy the application requirements of accurate observation. Finally, general image enhancement algorithms introduce unnecessary artifacts. In order to better observe and analyze the morphological structure of flyers, a special image enhancement algorithm is needed to improve the image quality.

Aiming at the problems of single-shot X-ray radiograph via ultrafast laser with high background noise interference, low contrast, and difficulties in morphology identification and measurement, an improved histogram equalization image enhancement algorithm based on multi-scale fusion (IHEMF) is proposed in this paper. The conventional CLAHE algorithm uses a fixed clipping threshold, which leads to excessive enhancement of the background region. The IHEMF algorithm modifies the fixed clipping threshold of the CLAHE algorithm to a gradient-dependent parameter. By calculating the horizontal gradient and vertical gradient of each block sub-region in the original image and bringing them into the constructed Gaussian function, adaptive clipping thresholds that can better fit different regional features are obtained. At the same time, in order to avoid the halo phenomenon in the light-dark boundary region, the brightness weight and gradient weight of the original image and the enhanced image by the improved CLAHE algorithm are first calculated, and then the fused images are obtained by pyramid decomposition and reconstruction. When the contrast and shape of the flyer are enhanced, the noise is also amplified. To reduce the effects of plasma and quantum noise in the fused image, block matching 3D (BM3D) denoising algorithm is employed. A three-channel flyer image is obtained by adding pseudo-color to the denoised image in order to obtain better visual effects. In order to verify the effectiveness of the IHEMF algorithm, the enhancement experiments of the static, dynamic and final state images are carried out and the results are compared with those of the commonly used algorithms such as HE, CLAHE, MSR, cl-BHE, ROPE and FCCE.

We tested the performance of the IHEMF algorithm using static, dynamic and final state images [Figs. 4(a), 5(a) and 6(a)]. The results for three typical images show that the morphology processed by IHEMF algorithm [e.g., Fig. 4(h)] is clearly visible, while other algorithms such as HE, CLAHE, MSR, cl-BHE, ROPE and FCCE [e.g., Figs. 4(b)?4(g)] have little enhancement effect (the material inside the metal cavity cannot be seen). In addition, the images processed by other algorithms have disadvantages such as excessive enhancement in the background area, halo phenomenon at the image edges and strong plasma interference, which are not suitable for observation. IHEMF algorithm reduces the influence of plasma and halos, and the shape of the flyer in the processed image [Figs. 4(h), 5(h) and 6(h)] is clearly visible. The contrast noise ratio (CNR) indicates the ability to distinguish the region of interest (ROI) from the background region, which is used to evaluate the image enhancement effect of the algorithm. The CNR of the images processed by the IHEMF algorithm is significantly improved over the CNR of the original images and the increasing rate is much higher than those of the other algorithms (Table 1), such as HE, CLAHE, MSR, cl-BHE, ROPE and FCCE. Experimental results for three typical images show that the IHEMF algorithm improves the contrast of the ROI and has better enhancement performance compared with other classical image enhancement algorithms.

In this paper, we describe an improved histogram equalization image enhancement algorithm combined with multi-scale fusion. The algorithm combines the enhancement characteristics of the improved CLAHE algorithm and the structural retention characteristics of the pyramid fusion algorithm, and the BM3D algorithm is used in order to reduce plasma effects. The research shows that the proposed method can effectively suppress image artifacts and noise (halos and plasma), enhance the contrast of X-ray images, and significantly improve the visual effect. Compared with the original image, the CNR of the image processed by the IHEMF algorithm is significantly improved, and the increasing rate is much higher than those of the other algorithms. The IHEMF algorithm greatly improves the contrast and image quality of the ROI and lays the foundation for accurately obtaining characterization parameters such as internal structure and planarity of the flyer from single-shot X-ray radiograph via ultrafast laser.