Performance Assessment of Image Compression and Reconstruction Employing Wavelet Transform with Lifting Scheme: An Effective Approach (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2022)
In the analysis for image compression and subsequent reconstruction, the primary objective is tominimize the data redundancy in terms of spatial and frequency domain without much affectingthe image quality. Lossless reversible image compression model is proposed in case ofcontinuous and discrete time utilizing integer wavelet transform (IWT) that incorporates liftingscheme (LS) excellently. As compared to wavelet decomposition, here both approximation aswell as detailed contents of the image under consideration are further decomposed, whichenhances the compression ratio. Bi-orthogonal wavelets are constructed using LS that makes useof both high pass and low pass filter values along with addition and shift operations on theresulting wavelet coefficients quite suitably. Forward as well as inverse lifting schemes areimplemented to reduce the computational complexity and achieve superior image compressionperformance that accounts for encoding time, decoding time, peak signal to noise ratio (PSNR)and better compression ratio (CR). The present paper projects the utility of IWT and LS in thedomain of image compression and reconstruction that will immensely benefit the researchers andexperimentalists involved with image and signal processing.