Image Compression Based on 2D Dual Tree Complex Wavelet Transform (2D DT-CWT)


By removing the redundant data, the image can be represented in a smallernumber of bits and hence can be compressed. There are many different methods ofimage compression. This paper investigates a proposed form of compression based on2D Dual Tree complex wavelet transform (2D DT-CWT). Many wavelet coefficientsare closed to zero. Thresholding can modify the coefficients to produce more zerosthat are allowed a higher compression rate. The wavelet analysis does not actuallycompress a signal. Therefore Huffman coding is used with a signal processed by thewavelet analysis in order to compress data. Wide range of threshold values is used inthe proposed form. From the results the proposed form give higher rate ofcompression and lower RMS error compared with that forms based on DiscreteWavelet Transform (DWT), Dual Tree Real Wavelet Transform (DT-RWT) and thewell known method based Discrete Cosine Transform (DCT).