2D Dual-Tree Complex Wavelet Transform Based Image Analysis

Data compression is important in storage and transmission of information. Especially digital image compression is important due to the high storage and transmission requirements. By removing the redundant data, the image can be represented in a smaller number of bits and hence can be compressed. Various compression techniques have been proposed in recent years to achieve good compression. This paper investigates a proposed form of compression based on 2D Dual Tree Complex Wavelet Transform (2D DT-CWT), which results in many wavelet coefficients close to zero. Even the Thresholding can modify the coefficients to produce more zeros which allow a higher compression ratio. The wavelet analysis alone does not actually compress a signal. Therefore one of the coding techniques called Huffman coding is used along with wavelet analysis of an image in order to compress the data. Wide range of threshold values is used in the proposed form. From the results we can say that the proposed form give higher rate of compression and lower RMS error compared with that of other forms based on Discrete Wavelet Transform (DWT).