Underwater fluorescence imaging technology is extensively utilized in various fields, including environmental monitoring, marine biological research, and marine energy exploration. However, underwater fluorescence imaging often suffers from insufficient contrast and noise interference due to the absorption and scattering of light in water, as well as other complex optical environmental factors. Because of their significant impact on image quality and subsequent analysis, there is an urgent need to develop techniques for underwater image enhancement and restoration to mitigate these effects.The underwater fluorescence imaging detector, which primarily consists of an optical detection unit, a power supply and drive unit, and a control and data processing unit (Fig.3). Compared the two fluorescence signals and the two signal-to-noise ratios (SNR) of images of which the results were calculated with and without calibration serves to evaluate the effectiveness of the calibration method (Fig.5). The detection limit of the device was also tested to evaluate its performance in aquatic environments (Fig.6).The fluorescence signal intensity distribution becomes more uniform and the noise is significantly reduced after correction (Fig.7). The SNR of the image is also improved at various exposure times (Fig.8). In the underwater test, compared with the uncorrected fluorescence image of the Rhodamine B (RhB) solution, the fluorescence signal in the corrected image has been enhanced. Additionally, the contrast between the target and the background is significantly improved (Fig.9). The fluorescence signal diagram clearly illustrates a gradient distribution after correction (Fig.10). The underwater fluorescence imaging device developed in this work gained good performance with a quantification range from 130 µg/L to 910 µg/L and a detection limit low to 40 µg/L (Fig.11).The experimental results show that the image correction method based on standardized coefficients not only effectively eliminates the fluorescence variations caused by the uneven intensity of excitation light, but also reduces the noise generated by the attenuation of light in the water, which in turn improves the images’ SNR. In the underwater test, the fluorescence signal of the corrected RhB solution was enhanced, the contrast was improved, and the fluorescence signal images could be reflected the concentration change. The fluorescence imaging device gained a detection limit of 40 µg/L and a quantification range of 130-910 µg/L, providing high-quality images for underwater environmental monitoring and biological research. In the subsequent research, the signal processing algorithm can be further optimized by an artificial intelligence training set, which in turn reduces the detection limit of the device and widens its linear range. By optimizing the correction algorithm, the detector is expected to be widely used in underwater imaging scenarios.