Distributed processing is carried out in parallel, which reduces processing time. This enables fast and efficient processing of raster and vector digital data in a computer cluster environment, saving time and resources.
The ability to handle georeferenced raster and vector data makes this innovation valuable for applications that require combining these types of information.
The spatial conflict resolution operation guarantees an accurate representation of image objects in areas of overlap, improving the quality of the results.
The invention makes it possible to process large sets of image data on computer clusters of any size.
The growing volume of digital image data has brought challenges for efficient processing by conventional systems, which are limited in terms of computational and storage resources. Existing solutions do not adequately address the processing of georeferenced images and the combination of raster and vector data, leaving significant gaps in digital image processing.
The present invention introduces an innovative method for supporting the processing of raster and vector data in computer clusters. It addresses the indexing of image parts and objects, the association of objects to geocells and distributed processing strategies. This enables efficient manipulation of digital data in a variety of applications, from remote sensing to radiography, magnetic resonance imaging and microscopy.
Raster images are divided into image parts, which are distributed across the cluster nodes according to the policies of the distributed file system. The image objects are stored in the distributed file system and replicated in the cluster.
Distributed processing is carried out according to different strategies, depending on the characteristics of the system. This ensures that processing is efficient, maintaining data integrity and taking spatial locality into account.
Patent title:
Method that supports the analysis of digital images in a computer cluster environment
Deposit Number:
BR 11 2017 026499 4
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