Image compression based on 2D dual tree complex wavelet transform (2D DT-CWT)‎

Abstract EN

By removing the redundant data, the image can be represented in a smaller number of bits and hence can be compressed.

There are many different methods of image compression.

This paper investigates a proposed form of compression based on 2D Dual Tree complex wavelet transform (2D DT-CWT).

Many wavelet coefficients are closed to zero.

Thresholding can modify the coefficients to produce more zeros that are allowed a higher compression rate.

The wavelet analysis does not actually compress a signal.

Therefore Huffman coding is used with a signal processed by the wavelet analysis in order to compress data.

Wide range of threshold values is used in the proposed form.

From the results the proposed form give higher rate of compression and lower RMS error compared with that forms based on Discrete Wavelet Transform (DWT), Dual Tree Real Wavelet Transform (DT-RWT) and the well known method based Discrete Cosine Transform (DCT).