# An Improved SIFT Underwater Image Stitching Method
## 1 Introduction  
The process of stitching underwater images finds extensive applications in the realms of undersea exploration, marine archaeology, marine biological research, and the visualization of wrecks. Underwater conditions are characterized by the attenuation and backscattering of light, which restricts the field of view that cameras can capture. Consequently, it becomes unfeasible to encompass a larger area within a single frame. Nonetheless, panoramic imaging offers a solution by amalgamating images from diverse viewpoints into a single composite image that spans a wider area [1]. This approach furnishes a more comprehensive reservoir of image data for subsequent research endeavors. In recent years, significant advancements have been made in the fields of image stitching, mosaic construction, and full three-dimensional (3D) reconstruction. However, it is important to emphasize that these methods are primarily designed for terrestrial scenarios and do not directly address the unique challenges encountered in underwater imaging [2]. Underwater image stitching presents distinct challenges compared to its land-based counterpart. The first major challenge lies in obtaining clear underwater images, given the complex and dynamic underwater environment. Underwater images are susceptible to blurring caused by water flow and the presence of microorganisms in the aquatic medium [3]. The second challenge is associated with the complexity of underwater subjects. Underwater elements such as marine life, rocks, and wrecks often lack distinct texture features, resulting in blurry outlines that are difficult to extract. Additionally, marine organisms like seaweed, oysters, sea snails, earthworms, and sea grass can attach toshipwrecks, further obscuring their outlines and features. This complicates the accuracy of feature matching. Furthermore, the movement of marine life due to water currents can introduce alignment errors and ghosting artifacts in underwater images. The third challenge pertains to the prevalence of flat areas in underwater images, especially on extensive ocean floors [4]. These regions exhibit similar textures around feature points, making it challenging to extract effective feature points. The fourth challenge is related to the assumptions underlying mosaic construction techniques, which often assume that the images are captured by a purely rotating camera, or that the scene is planar [5]. These assumptions imply the absence of parallax caused by camera movement and a lack of three-dimensional effects. However, underwater images are subject to light attenuation and backscattering, which can result in significant distortions in the mosaic. These distortions undermine the applicability of these assumptions in underwater contexts. To address the challenges of underwater image stitching, in recent years, many researchers have conducted work on underwater image stitching and video stitching. Underwater mosaicking has predominantly been explored within the realm of vision-based navigation and maintaining a stable position near the seafloor [6]. However, these approaches are typically tailored to specific conditions and are unable to seamlessly stitch together any set of acquired images without external guidance [7]. When it comes to underwater images captured by divers, they often lack the regularity of fixed time or distance intervals, and sensor data are often unavailable. Consequently, to facilitate the stitching of arbitrary underwater images, many researchers have turned to image registration methods like SIFT and SURF. These methods rely solely on image information and do not necessitate the use of detection devices or impose any special requirements specific to underwater images. Nonetheless, it is important to note that these image stitching methods heavily hinge on the information derived from matching pairs of distinctive image features. This reliance places significant demands on both the quantity and accuracy of these feature matches [8].