LEADER 04211nam 22005775 450 001 9910298572903321 005 20200705154413.0 010 $a3-319-05558-5 024 7 $a10.1007/978-3-319-05558-9 035 $a(CKB)2560000000148865 035 $a(EBL)1697752 035 $a(OCoLC)880460437 035 $a(SSID)ssj0001199746 035 $a(PQKBManifestationID)11658147 035 $a(PQKBTitleCode)TC0001199746 035 $a(PQKBWorkID)11205241 035 $a(PQKB)10759866 035 $a(MiAaPQ)EBC1697752 035 $a(DE-He213)978-3-319-05558-9 035 $z(PPN)258861355 035 $a(PPN)178318841 035 $a(EXLCZ)992560000000148865 100 $a20140405d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aImage Blending Techniques and their Application in Underwater Mosaicing /$fby Ricard Prados, Rafael Garcia, László Neumann 205 $a1st ed. 2014. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014. 215 $a1 online resource (115 p.) 225 1 $aSpringerBriefs in Computer Science,$x2191-5768 300 $aDescription based upon print version of record. 311 $a3-319-05557-7 320 $aIncludes bibliographical references. 327 $aIntroduction -- Underwater 2D Mosaicing -- State of the Art in Image Blending Techniques -- Proposed Framework -- Results -- Conclusions. 330 $aUnderwater surveys have numerous scientific applications, and optical imaging by underwater vehicles can provide high-resolution visual information of the ocean floor. However, the particular challenges of the underwater medium, such as light attenuation, require the imaging to be performed as close to the seabed as possible. Hence, optically mapping large seafloor areas can only be achieved by building image mosaics from a set of reduced-area pictures. Unfortunately, the seams along image boundaries are often noticeable, requiring image blending, the merging step in which these artifacts are minimized. Yet processing tools and bottlenecks have restricted underwater photo-mosaics to small areas despite the hundreds of thousands of square meters that modern surveys can cover. This work proposes strategies and solutions to tackle the problem of building photo-mosaics of very large underwater optical surveys, presenting contributions to the image preprocessing, enhancing and blending steps, and resulting in an improved visual quality of the final photo-mosaic. The text opens with a comprehensive review of mosaicing and blending techniques, before proposing an approach for large scale underwater image mosaicing and blending. In the image preprocessing step, a depth dependent illumination compensation function is used to solve the non-uniform illumination appearance due to light attenuation. For image enhancement, the image contrast variability due to different acquisition altitudes is compensated using an adaptive contrast enhancement based on an image quality reference selected through a total variation criterion. In the blending step, a graph-cut strategy operating in the image gradient domain over the overlapping regions is suggested. Next, an out-of-core blending strategy for very large scale photo-mosaics is presented and tested on real data. Finally, the performance of the approach is evaluated and compared with other approaches. 410 0$aSpringerBriefs in Computer Science,$x2191-5768 606 $aOptical data processing 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 615 0$aOptical data processing. 615 14$aImage Processing and Computer Vision. 676 $a621.367 700 $aPrados$b Ricard$4aut$4http://id.loc.gov/vocabulary/relators/aut$0918909 702 $aGarcia$b Rafael$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aNeumann$b László$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910298572903321 996 $aImage Blending Techniques and their Application in Underwater Mosaicing$92060902 997 $aUNINA