A comparative analysis among dual tree complex wavelet and other wavelet transforms based on image compression

Recently, the demand for efficient image compression algorithms have peeked due to storing and transmitting image requirements over long distance communication purposes. Image applications are now highly prominent in multimedia production, medical imaging, law enforcement forensics and defense industries. Hence, effective image compression offers the ability to record, store, transmit and analyze images for these applications in a very efficient manner. This paper offers a comparative analysis between the Dual Tree Complex Wavelet Transform (DTCWT) and other wavelet transforms such as Embedded Zerotree Wavelet (EZW), Spatial orientation Transform Wavelet (STW) and Lifting Wavelet Transform (LWT) for compressing gray scale images. The performances of these transforms will be compared by using objective measures such as peak signal to noise ratio (PSNR), mean squared error (MSE), compression ratio (CR), bit per pixel (BPP) and computational time (CT). The experimental results show that DTCWT provides better performance in term of PSNR and MSE and better reconstruction of image than other methods