Efficiency-Accuracy Trade-Off in Light Field Estimation with Cost Volume Construction and Aggregation.

The Rich spatial and angular information in light field images enables accurate depth estimation, which is a crucial aspect of environmental perception. However, the abundance of light field information also leads to high computational costs and memory pressure. Typically, selectively pruning some light field information can significantly improve computational efficiency but at the expense of reduced depth estimation accuracy in the pruned model, especially in low-texture regions and occluded areas where angular diversity is reduced. In this study, we propose a lightweight disparity estimation model that balances speed and accuracy and enhances depth estimation accuracy in textureless regions. We combined cost matching methods based on absolute difference and correlation to construct cost volumes, improving both accuracy and robustness. Additionally, we developed a multi-scale disparity cost fusion architecture, employing 3D convolutions and a UNet-like structure to handle matching costs at different depth scales. This method effectively integrates information across scales, utilizing the UNet structure for efficient fusion and completion of cost volumes, thus yielding more precise depth maps. Extensive testing shows that our method achieves computational efficiency on par with the most efficient existing methods, yet with double the accuracy. Moreover, our approach achieves comparable accuracy to the current highest-accuracy methods but with an order of magnitude improvement in computational performance.

Underwater image enhancement based on zero-shot learning and level adjustment.

Light is scattered and partially absorbed while traveling through water, hence, underwater captured images often exhibit issues such as low contrast, detail blurring, color attenuation, and low illumination. To improve the visual performance of underwater imaging, herein, we propose a two-step method of zero-shot dehazing and level adjustment. In the newly developed approach, the original image is fed into a "zero-shot" dehazing network and further enhanced by an improved level adjustment methodology combined with auto-contrast. By conducting experiments, we then compare the performance of the proposed method with six classical state-of-the-art methods. The qualitative results confirm that the proposed method is capable of effectively removing haze, correcting color deviations, and maintaining the naturalness of images. We further perform a quantitative evaluation, revealing that the proposed method outperforms the comparison methods in terms of peak signal-to-noise ratio and structural similarity. The enhancement results are also measured by employing the underwater color image quality evaluation index (UCIQE), indicating that the proposed approach exhibits the highest mean values of 0.58 and 0.53 on the two data sets. The experimental results collectively validate the efficiency of the proposed methodology in enhancing underwater blurred images.

A Tightly Integrated Navigation Method of SINS, DVL, and PS Based on RIMM in the Complex Underwater Environment.

Navigation and positioning of autonomous underwater vehicles (AUVs) in the complex and changeable marine environment are crucial and challenging. For the positioning of AUVs, the integrated navigation of the strap-down inertial navigation system (SINS), Doppler velocity log (DVL), and pressure sensor (PS) has a common application. Nevertheless, in the complex underwater environment, the DVL performance is affected by the current and complex terrain environments. The outliers in sensor observations also have a substantial adverse effect on the AUV positioning accuracy. To address these issues, in this paper, a novel tightly integrated navigation model of the SINS, DVL, and PS is established. In contrast to the traditional SINS, DVL, and PS tightly integrated navigation methods, the proposed method in this paper is based on the velocity variation of the DVL beam by applying the DVL bottom-track and water-track models. Furthermore, a new robust interacting multiple models (RIMM) information fusion algorithm is proposed. In this algorithm, DVL beam anomaly is detected, and the Markov transfer probability matrix is accordingly updated to enable quick model matching. By simulating the motion of the AUV in a complex underwater environment, we also compare the performance of the traditional loosely integrated navigation (TLIN) model, the tightly integrated navigation (TTIN) model, and the IMM algorithm. The simulation results show that because of the PS, the velocity and height in the up-change amplitude of the four algorithms are small. Compared with the TLIN algorithm in terms of maximum deviation of latitude and longitude, the RIMM algorithm also improves the accuracy by 39.1243 m and 26.4364 m, respectively. Furthermore, compared with the TTIN algorithm, the RIMM algorithm improves latitude and longitude accuracy by 1.8913 m and 11.8274 m, respectively. A comparison with IMM also shows that RIMM improves the accuracy of latitude and longitude by 1.1506 m and 7.2301 m, respectively. The results confirm that the proposed algorithm suppresses the observed noise and outliers of DVL and further achieves quick conversion between different DVL models while making full use of the effective information of the DVL beams. The proposed method also improves the navigation accuracy of AUVs in complex underwater environments.

Relationship between HLA-G gene polymorphism and the susceptibility of esophageal cancer in Kazakh and Han nationality in Xinjiang.

OBJECTIVE: To explore the association between polymorphism of the human leukocyte antigen G (HLA-G) and susceptibility of esophageal carcinoma (EC) in Kazakh and Han nationality in Xinjiang. METHODS: The 14 bp deletion/insertion (rs16375) and 0105N (rs41557518) of HLA-G genotyping were determined by PCR and PCR-RFLP, respectively in 239 patients and 467 controls. RESULTS: There was a 2.69-fold (P(c) = 0.04, 95% CI: 1.30-5.55) increased risk of developing EC in individuals with the -14 bp/-14 bp genotype (rs16375) compared with those carrying +14 bp/+14 bp genotype in Kazakh after Bonferroni correction, there was no association of 0105N (rs41557518) both in Kazak and Han population. And there was a 2.82-fold (P(c) = 0.04, 95% CI: 1.32-6.04) increased risk of developing EC in individuals with -14 bp/-14 bp and C/C genotypes compared with those who had +14 bp/+14 bp and C/C genotypes in Kazakh. CONCLUSIONS: The study demonstrates that EC is associated with polymorphism of HLA-G14 bp in Chinese Kazak population. The 14 bp deletion/insertion of HLA-G gene may play a role in EC susceptibility of Kazakh.