Abstract
The development and application of image data has the characteristics of high resolution, large data volume and so on. Research on how to take advantage of MapReduce to distributed processing efficient and fast is one of the focuses and hotspots in the field of massive image data management. To solve the above problems, combing efficient distributed programming and running frame provided by MapReduce model and image pyramid algorithm, proposing and realizing a distributed model for massive image data. Experiment expresses that this model is good performance in massive image’s browsing and rooming.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
