Underwater Image Enhancement before Three-Dimensional (3D) Reconstruction and Orthoimage Production Steps: Is It Worth?

The advancement of contemporary digital techniques has greatly facilitated the implementation of digital cameras in many scientific applications, including the documentation of Cultural Heritage. Digital imaging has also gone underwater, as many cultural heritage assets lie in the bottom of water bodies. Consequently, a lot of imaging problems have arisen from this very fact. Some of them are purely geometrical, but most of them concern the quality of the imagery, especially in deep waters. In this paper, the problem of enhancing the radiometric quality of underwater images is addressed, especially for cases where this imagery is going to be used for automated photogrammetric and computer vision algorithms later. In detail, it is investigated whether it is worth correcting the radiometry of the imagery before the implementation of the various automations or not, the alternative being to radiometrically correct the final orthoimage. Two different test sites were used to capture imagery ensuring different environmental conditions, depth, and complexity. The algorithms investigated to correct the radiometry are a very simple automated method, using Adobe Photoshop®, a specially developed colour correction algorithm using the CLAHE (Zuiderveld, 1994) method, and an implementation of the algorithm, as described in Bianco et al. (2015). The corrected imagery is afterwards used to produce point clouds, which in turn are compared and evaluated.

[1]  Diego González-Aguilera,et al.  Development of an All-Purpose Free Photogrammetric Tool , 2016 .

[2]  Karel J. Zuiderveld,et al.  Contrast Limited Adaptive Histogram Equalization , 1994, Graphics Gems.

[3]  Weilin Hou,et al.  Imagery-derived modulation transfer function and its applications for underwater imaging , 2007, SPIE Optical Engineering + Applications.

[4]  Fabio Bruno,et al.  Development and integration of digital technologies addressed to raise awareness and access to European underwater cultural heritage. An overview of the H2020 i-MARECULTURE project , 2017, OCEANS 2017 - Aberdeen.

[5]  M. S. Hitam,et al.  Mixture contrast limited adaptive histogram equalization for underwater image enhancement , 2013, 2013 International Conference on Computer Applications Technology (ICCAT).

[6]  Uwe von Lukas Underwater Visual Computing: The Grand Challenge Just around the Corner , 2016, IEEE Computer Graphics and Applications.

[7]  Matthew Johnson-Roberson,et al.  Mapping Submerged Archaeological Sites using Stereo‐Vision Photogrammetry , 2013 .

[8]  Puran Gour,et al.  Analysis of Contrast Enhancement Techniques For Underwater Image , .

[9]  Dimitrios Skarlatos,et al.  THE EFFECT OF UNDERWATER IMAGERY RADIOMETRY ON 3DRECONSTRUCTION AND ORTHOIMAGERY , 2017 .

[10]  R. A. Salam,et al.  Underwater Image Enhancement Using an Integrated Colour Model , 2007 .

[11]  Puran Gour,et al.  Underwater Image Segmentation using CLAHE Enhancement and Thresholding , 2012 .

[12]  Djamel Merad,et al.  Underwater image preprocessing for automated photogrammetry in high turbidity water: An application on the Arles-Rhone XIII roman wreck in the Rhodano river, France , 2012, 2012 18th International Conference on Virtual Systems and Multimedia.

[13]  L. Neumann,et al.  a New Color Correction Method for Underwater Imaging , 2015 .

[14]  Stella Demesticha,et al.  The 4th‐Century‐BC Mazotos Shipwreck, Cyprus: a preliminary report , 2011 .

[15]  Pierre Drap,et al.  Underwater Photogrammetry for Archaeology , 2012 .

[16]  Yoav Y. Schechner,et al.  Active Polarization Descattering , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Oscar Pizarro,et al.  High‐Resolution Underwater Robotic Vision‐Based Mapping and Three‐Dimensional Reconstruction for Archaeology , 2017, J. Field Robotics.