Development of a multi-excitation fluorescence (MEF) imaging method to improve the information content of benthic coral reef surveys

Benthic surveys are a key component of monitoring and conservation efforts for coral reefs worldwide. While traditional image-based surveys rely on manual annotation of photographs to characterise benthic composition, automatic image annotation based on computer vision is becoming increasingly common. However, accurate classification of some benthic groups from reflectance images presents a challenge to local ecologists and computers alike. Most coral reef organisms produce one or a combination of fluorescent pigments, such as Green Fluorescent Protein (GFP)-like proteins found in corals, chlorophyll-a found in all photosynthetic organisms, and phycobiliproteins found in red macroalgae, crustose coralline algae (CCA) and cyanobacteria. Building on the potential of these pigments as a target for automatic image annotation, we developed a novel imaging method based on off-the-shelf components to improve classification of coral and other biotic substrates using a multi-excitation fluoresce...底栖生物调查是全球珊瑚礁监测与保护工作的核心组成部分。传统基于图像的调查依赖对照片进行人工标注以表征底栖生物组成，而基于计算机视觉的自动图像标注正愈发普及。然而，从反射率图像中精准分类部分底栖类群，对本地生态学家与计算机系统而言均是挑战。多数珊瑚礁生物可产生一种或多种荧光色素组合，例如珊瑚体内的类绿色荧光蛋白（Green Fluorescent Protein, GFP）、所有光合生物均含有的叶绿素a，以及红藻大型藻类、结壳珊瑚藻（CCA）与蓝细菌中存在的藻胆蛋白。基于这些色素作为自动图像标注靶点的潜力，我们开发了一种基于商用现成组件的新型成像方法，以提升珊瑚与其他生物基质的分类精度，该方法采用多激发荧光