Unmanned underwater operations using remotely operated vehicles or unmanned surface vehicles are increasing in recent times, and this guarantees human safety and work efficiency. Optical cameras and multi-beam sonars are generally used as imaging sensors in underwater environments. However, the obtained underwater images are difficult to understand intuitively, owing to noise and distortion. In this study, we developed an optical and sonar image fusion system that integrates the color and distance information from two different images. The enhanced optical and sonar images were fused using calibrated transformation matrices, and the underwater image quality measure (UIQM) and underwater color image quality evaluation (UCIQE) were used as metrics to evaluate the performance of the proposed system. Compared with the original underwater image, image fusion increased the mean UIQM and UCIQE by 94% and 27%, respectively. The contrast-to-noise ratio was increased six times after applying the median filter and gamma correction. The fused image in sonar image coordinates showed qualitatively good spatial agreement and the average IoU was 75% between the optical and sonar pixels in the fused images. The optical-sonar fusion system will help to visualize and understand well underwater situations with color and distance information for unmanned works.
Keywords: geometric calibration of multi-imaging systems; image fusion; optical and sonar image fusion system; single-image enhancement; underwater visualization.