• Improving underwater visibility using vignetting correction

      Sooknanan, K.; Kokaram, A.; Baugh, G.; Corrigan, D.; Wilson, J.; Harte, N. (IEEE, 2012)
      Underwater survey videos of the seafloor are usually plagued with heavy vignetting (radial falloff) outside of the light source beam footprint on the seabed. In this paper we propose a novel multi-frame approach for removing this vignetting phenomenon which involves estimating the light source footprint on the seafloor, and the parameters for our proposed vignetting model. This estimation is accomplished in a bayesian framework with an iterative SVD-based optimization. Within the footprint, we leave the image contents as is, whereas outside this region, we perform vignetting correction. Our approach does not require images with different exposure values or recovery of the camera response function, and is entirely based on the attenuation experienced by point correspondences accross multiple frames. We verify our algorithm with both synthetic and real data, and then compare it with an existing technique. Results obtained show significant improvement in the fidelity of the restored images.
    • Indexing and selection of well-lit details in underwater video using vignetting estimation

      Sooknanan, K.; Kokaram, A.; Corrigan, D.; Wilson, J.; Harte, N. (IEEE, 2012)
      Video is an important tool in underwater surveys today, yet its useful field of view is restricted to image details within well lit regions on the seafloor. In this paper we present a novel vignetting-based weighting scheme for selecting these well lit details for use in the creation of a wide area view (mosaic) of the surveyed seafloor. Apart from this detail selection novelity,two other contributions are made. Firstly, because some of these scenes contain very little image texture, we introduce a hybrid homography estimation procedure that uses both feature-based and exhaustive searching techniques. Secondly, to facilitate cross referencing with the video, sections of the mosaic were indexed with the frame number in which the respective image details was selected from. We test our algorithm with real seabed survey video, whose scientific mission was population census of the particular species of lobster, Nephrops norvegicus. High quality mosaics were obtained that captured image details from well lit regions of the scene, which expert marine biologists agreed was a useful analysis tool. This work was supported by the Science Foundation Ireland PI Programme: SFI-PI 08/IN.1/I2112, and was done in collaboration with the Marine Institute Galway.