VLSI Design of 2-D Discrete Wavelet Transform for Area-Efficient and High- Speed Image Computing - PDR Presentor: Eyal Vakrat Instructor: Tsachi Martsiano

Table of content Background Project goals Project milestones Block diagram Micro-architecture Algorithm Development environments Gantt

Background What is DWT? What is the DWT used for? Why should we use the DWT? - Lossy vs. Lossless compression conspros May cause blurring or ringing near edges May cost a bit more Multi resolution - Allows good orientation both in time and frequency domain Fast DWT Single resolution slower Smaller Error Simpler DFT

Project goals – Implementation of high-speed and real-time 2-D Discrete Wavelet Transform – Based on new and fast convolution approach – Efficient memory area (in-place) – Article I use: World Academy of Science, Engineering and Technology , VLSI Design of 2-D Discrete Wavelet Transform for Area-Efficient and High-Speed Image Computing, by Mountassar Maamoun, Mehdi Neggazi, Abdelhamid Meraghni, and Daoud Berkani.

Project milestones – Learn the 2D-DWT algorithm from the article – Write floating point MATLAB DWT and IDWT Choose coefficients Compare the results to MATLAB DWT function – Write fixed point MATLAB DWT and IDWT Compare the results to MATLAB DWT function Select the fixed point resolution – Architecture: Learn the proposed architecture from the paper Adjust it to our case - different coefficients and picture size – Code the module in VHDL – Simulate the module using ModelSim – Synthesis of the module using Quartus

Top Block Diagram memory

Micro-architecture

Algorithm

Development environments MATLAB - modeling MODELSIM -simulation QUARTUS - synthesis

Gantt

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