拼接深水图像

Kuldeep Purohit, Subeesh Vasu, A. Rajagopalan, V. Jyothi, Ramesh Raju
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引用次数: 3

摘要

许多来源的失真使得水下(UW)图像的拼接非常具有挑战性的努力。可以处理常规照片(地面/空中)的方法无法在UW图像上提供所需的结果。考虑到水下退化的来源是确保质量性能的核心。本文所描述的工作专门针对远程操作车辆(rov)捕获的深紫外图像的拼接问题。这些图像主要受到雾霾、颜色变化和不均匀光照的影响。我们提出了一个框架,恢复这些图像按照一个适当的派生退化模型。此外,我们的方案利用每个图像中存在的场景几何信息来帮助构建一个没有局部模糊、重影、双重轮廓和可见接缝等人工制品的马赛克。在真实的水下图像序列上进行了几个实验,以证明我们的拼接管道的性能并进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mosaicing deep underwater imagery
Numerous sources of distortions render mosaicing of underwater (UW) images an immensely challenging effort. Methods that can process conventional photographs (terrestrial/aerial) fail to deliver the desired results on UW images. Taking the sources of underwater degradations into account is central to ensuring quality performance. The work described in this paper specifically deals with the problem of mosaicing deep UW images captured by Remotely Operated Vehicles (ROVs). These images are mainly degraded by haze, color changes, and non-uniform illumination. We propose a framework that restores these images in accordance with a suitably derived degradation model. Furthermore, our scheme harnesses the scene geometry information present in each image to aid in constructing a mosaic that is free from artifacts such as local blurring, ghosting, double contouring and visible seams. Several experiments on real underwater images sequences have been carried out to demonstrate the performance of our mosaicing pipeline along with comparisons.
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