An Efficient Algorithm and Architecture Design For Two-Dimension Separable Discrete Wavelet Transform

In recent years, the Discrete Wavelet Transform (DWT) has become a powerful tool in many areas, such as image compression and analysis, texture discrimination, fractal analysis, pattern recognition and so on. Due to the localization property both in time and frequency domain, wavelet transform is more efficient than Short Time Fourier Transform (STFT) or Discrete Cosine Transform (DCT) in de-correlating the time domain signal correlation. Also, it has been proved that the wavelet based image compression scheme has better performance than that with DCT based especially in very low bit rate. Due to these advantages, the DWT has been included in the coming JPEG2000 and MPEG4 standards. In this thesis, we focus on the still image compression application of wavelet transform. We will give a brief introduction of wavelet transform and describe the proposed Circular-Parallel architecture (CPA) for 2-D DWT computation in detail. In addition, some wavelet based coding algorithms are presented in this thesis. From these coding algorithms, we can clearly understand the role of DWT module in the overall system. This helps us to design the I/O of the DWT module such that it can incorporate with the other modules in the system without too much additional effort. The key point of the proposed architecture is to exploit the dependence of different filter bank coefficients and further to schedule the computation order of these coefficients based on the dependence. As compared with some previously proposed architectures, our architecture has simpler memory I/O interface and lower hardware cost. And it can process the 2-D DWT in line by line fashion that is suitable for many real-time image coding applications. Based on TSMC SPTM 0.6um process technology, we use COMPASS 0.6um high performance cell library to implement the proposed CPA architecture. The chip integrates about 44k gates in 5.4mm x 5.3mm silicon area with the capability to process 8-tap filter and 12.5 MHz input sample rate that can meet many image and videoconference real-time applications.