Energy and Area Efficient Approximate Image Compression Technique using Discrete Wavelet Transform 2D DWT and VLSI

Electronics & Communication Engineering

In this study, the wavelet-based VLSI architecture for image compression is studied. The most popular method of picture compression is discrete wavelet transform, which is also the most effective algorithm for JPEG image compression. A discrete wavelet architecture is suggested that can do both forward and inverse lifting. As an improved approach, lifting scheme is utilized instead of the conventional method, which needs more memory, space, and power. The DWT architecture, a potent image compression technique, is developed using a lifting-based strategy. Reduced memory referencing, low power consumption, low latency, and high throughput are all benefits of this architecture. In a manner similar to this, the Inverse Discrete Wavelet Transform (IDWT) is also obtained to obtain the visual matrix. Both lossy and lossless compression can be achieved using the concept. Linear algebra views of DWT and IDWT have been used to simplify the design. The hardware optimization, quick computation times, consistent data flow, and decreased complexity of the suggested architecture are its benefits. The proposed architecture can easily be scaled with the filter length and 2D DWT level due to its regular nature. The 2D DWT VLSI architecture is built with FPGA in VHDL. Applications that employ a lot of picture and video coding are becoming more and more popular, making this a busy and dynamic sector. A foundation for study and development is provided by Image and Video Compression for Multimedia Engineering.

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