Cargando…

Image Blending Techniques and their Application in Underwater Mosaicing

Underwater 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...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Prados, Ricard (Autor), Garcia, Rafael (Autor), Neumann, László (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2014.
Edición:1st ed. 2014.
Colección:SpringerBriefs in Computer Science,
Temas:
Acceso en línea:Texto Completo

MARC

LEADER 00000nam a22000005i 4500
001 978-3-319-05558-9
003 DE-He213
005 20220116225815.0
007 cr nn 008mamaa
008 140405s2014 sz | s |||| 0|eng d
020 |a 9783319055589  |9 978-3-319-05558-9 
024 7 |a 10.1007/978-3-319-05558-9  |2 doi 
050 4 |a TA1634 
072 7 |a UYQV  |2 bicssc 
072 7 |a COM012000  |2 bisacsh 
072 7 |a UYQV  |2 thema 
082 0 4 |a 006.37  |2 23 
100 1 |a Prados, Ricard.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Image Blending Techniques and their Application in Underwater Mosaicing  |h [electronic resource] /  |c by Ricard Prados, Rafael Garcia, László Neumann. 
250 |a 1st ed. 2014. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2014. 
300 |a XI, 107 p. 49 illus., 20 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a SpringerBriefs in Computer Science,  |x 2191-5776 
505 0 |a Introduction -- Underwater 2D Mosaicing -- State of the Art in Image Blending Techniques -- Proposed Framework -- Results -- Conclusions. 
520 |a Underwater 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 |a Computer vision. 
650 1 4 |a Computer Vision. 
700 1 |a Garcia, Rafael.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Neumann, László.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783319055596 
776 0 8 |i Printed edition:  |z 9783319055572 
830 0 |a SpringerBriefs in Computer Science,  |x 2191-5776 
856 4 0 |u https://doi.uam.elogim.com/10.1007/978-3-319-05558-9  |z Texto Completo 
912 |a ZDB-2-SCS 
912 |a ZDB-2-SXCS 
950 |a Computer Science (SpringerNature-11645) 
950 |a Computer Science (R0) (SpringerNature-43710)