000 03840nam a22005055i 4500
001 978-3-319-05558-9
003 DE-He213
005 20170628034129.0
007 cr nn 008mamaa
008 140405s2014 gw | s |||| 0|eng d
020 _a9783319055589
_9978-3-319-05558-9
024 7 _a10.1007/978-3-319-05558-9
_2doi
050 4 _aTA1637-1638
050 4 _aTA1637-1638
072 7 _aUYT
_2bicssc
072 7 _aUYQV
_2bicssc
072 7 _aCOM012000
_2bisacsh
072 7 _aCOM016000
_2bisacsh
082 0 4 _a006.6
_223
082 0 4 _a006.37
_223
100 1 _aPrados, Ricard.
_eauthor.
245 1 0 _aImage Blending Techniques and their Application in Underwater Mosaicing
_h[electronic resource] /
_cby Ricard Prados, Rafael Garcia, László Neumann.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXI, 107 p. 49 illus., 20 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Computer Science,
_x2191-5768
505 0 _aIntroduction -- Underwater 2D Mosaicing -- State of the Art in Image Blending Techniques -- Proposed Framework -- Results -- Conclusions.
520 _aUnderwater surveys have numerous scientific applications, and optical imaging by underwater vehicles can provide high-resolution visual information of the ocean floor. However, the particular challenges of the underwater medium, such as light attenuation, require the imaging to be performed as close to the seabed as possible. Hence, optically mapping large seafloor areas can only be achieved by building image mosaics from a set of reduced-area pictures. Unfortunately, the seams along image boundaries are often noticeable, requiring image blending, the merging step in which these artifacts are minimized. Yet processing tools and bottlenecks have restricted underwater photo-mosaics to small areas despite the hundreds of thousands of square meters that modern surveys can cover. This work proposes strategies and solutions to tackle the problem of building photo-mosaics of very large underwater optical surveys, presenting contributions to the image preprocessing, enhancing and blending steps, and resulting in an improved visual quality of the final photo-mosaic. The text opens with a comprehensive review of mosaicing and blending techniques, before proposing an approach for large scale underwater image mosaicing and blending. In the image preprocessing step, a depth dependent illumination compensation function is used to solve the non-uniform illumination appearance due to light attenuation. For image enhancement, the image contrast variability due to different acquisition altitudes is compensated using an adaptive contrast enhancement based on an image quality reference selected through a total variation criterion. In the blending step, a graph-cut strategy operating in the image gradient domain over the overlapping regions is suggested. Next, an out-of-core blending strategy for very large scale photo-mosaics is presented and tested on real data. Finally, the performance of the approach is evaluated and compared with other approaches.
650 0 _aComputer science.
650 0 _aComputer vision.
650 1 4 _aComputer Science.
650 2 4 _aImage Processing and Computer Vision.
700 1 _aGarcia, Rafael.
_eauthor.
700 1 _aNeumann, László.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319055572
830 0 _aSpringerBriefs in Computer Science,
_x2191-5768
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-05558-9
912 _aZDB-2-SCS
999 _c18432
_d18432