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In this study we present a two-step map/reduce framework to stitch satellite mosaic images. The proposed system enable recognition and extraction of objects whose parts falling in separate satellite mosaic images. However this is a time and resource consuming process. The major aim of the study is improving the performance of the image stitching processes … Read more
Abstract This paper proposes a new approach to solving the scalability problem in stitching and registration of satellite images. The image stitching process is mostly utilized to capture an image of an entire object, whose parts fall in separate but overlapping mosaics. Due to their high resolutions and huge sizes, the stitching of satellite mosaic … Read more
In this study we present a two-step map/reduce framework to stitch satellite mosaic images. The proposed system enable recognition and extraction of objects whose parts falling in separate satellite mosaic images. However this is a time and resource consuming process. The major aim of the study is improving the performance of the image stitching processes … Read more
In this study, we adopt image stitching process to bigdata frameworks. To do so, an algorithm is presented to merge two large images in accordance with Hadoop’s map/reduce computation paradigm. Images are first converted to bitmaps which are represented as matrices of 0s and 1s. The algorithm then finds the best possible match among two … Read more
This paper provides with the background of the research that will investigate into distributed and scalable big data framework for stitching of mosaic satellite images and object extraction. It has explained the motivation of the research and the methodologies and plan of work to be undertaken. The current stage of the research is focusing initially … Read more