Basel Abu-sinni

A small Glimpse into the world of Signal and Image Processing. This project allowed me to utilize a vastly used method for Adaptive Sampling, a technique which is also used in CG for Space Partitioning, Voxelization and Rendering.

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Adaptive Sampling methods instruct algorithms where to focus their computational resources, saving time and space, but unfortunately, finding the Optimal Sampling of a Signal is Hard. 

In this project, we are given an input Signal and a Bit Budget, I've implemented the QuadTree method which, at each iteration, decides wether it is beneficial to split some interval into 4 subintervals. The aim is to split where it matters and as much as the given Budget allows.

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The algorithm and its variations were implemented in Matlab and feature:

- Adaptive/Uniform Samplers

- 1D/2D Signals supported

- TopDown and BottomUp approaches

- Show Splits in Real-time

- Export Binary Representation of the Partitioning

- Plot QuadTree