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→Optimizing Image Processing using Intel's Data Analytics Library for Parallel computing and Vectorization
In this project we will be comparing Intel's Data Analytics Acceleration Library and OpenMP API to optimize image processing using parallel computing and vectorization. We selected two tasks for this project image sharpening and brightening. The run-time of each task is recorded and able to be compared by our demo program. We will also be comparing the implementation for each library.
In order to be able to more easily engage with image files, we will be utilizing the OpenCV library, leaning especially on the Mat class therein. The Mat class allows us to access the image as a n-dimensional array. Furthermore with our implementation we are able to rely on our parellelization choices instead of that built in to into the OpenCV library.
• Statistical analysis.
• Data visualization.
== '''OpenMP Implementation Summary''' ==