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Image Blending Techniques and their Application in Underwater Mosaicing

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TLDR
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.
Abstract
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.

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Journal ArticleDOI

A survey on image mosaicing techniques

TL;DR: An in-depth survey of the existing image mosaicing algorithms by classifying them into several groups, and the fundamental concepts are first explained and then the modifications made to the basic concepts by different researchers are explained.
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Optimal seamline detection for multiple image mosaicking via graph cuts

TL;DR: Experimental results on a large set of aerial, oblique and street-view panoramic images show that the proposed algorithm is capable of creating high-quality seamlines for multiple image mosaicking, while not crossing majority of visually obvious foreground objects and most of overlap regions with low image similarity.
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Image mosaicing: A deeper insight

TL;DR: An insight is provided into the existing mosaicing algorithms, along with their merits and shortcomings, and a comparison among various mosaicing methods is presented to find out which algorithm works best for a particular application and image type.
References
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