Parallax Effect Free Mosaicing of Underwater Video Sequence Based on Texture Features

TL;DR

This paper introduces a feature-based method for creating seamless underwater mosaics by minimizing parallax effects through local alignment and texture feature matching, improving image quality in challenging underwater environments.

Contribution

It presents a novel approach combining texture features and local alignment to effectively reduce parallax artifacts in underwater mosaicing.

Findings

Significant reduction of parallax artifacts in underwater mosaics.

Improved mosaic quality with minimized artifacts like blurring and ghosting.

Efficient frame selection reduces computational cost.

Abstract

In this paper, we present feature-based technique for construction of mosaic image from underwater video sequence, which suffers from parallax distortion due to propagation properties of light in the underwater environment. The most of the available mosaic tools and underwater image mosaicing techniques yields final result with some artifacts such as blurring, ghosting and seam due to presence of parallax in the input images. The removal of parallax from input images may not reduce its effects instead it must be corrected in successive steps of mosaicing. Thus, our approach minimizes the parallax effects by adopting an efficient local alignment technique after global registration. We extract texture features using Centre Symmetric Local Binary Pattern (CS-LBP) descriptor in order to find feature correspondences, which are used further for estimation of homography through RANSAC. In order to increase the accuracy of global registration, we perform preprocessing such as colour alignment between two selected frames based on colour distribution adjustment. Because of existence of 100% overlap in consecutive frames of underwater video, we select frames with minimum overlap based on mutual offset in order to reduce the computation cost during mosaicing. Our approach minimizes the parallax effects considerably in final mosaic constructed using our own underwater video sequences.