(untitled) (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2022)
In the analysis for image compression and subsequent reconstruction, the primary objective is to minimize the data redundancy in terms of spatial and frequency domain without much affecting the image quality. Lossless reversible image compression model is proposed in case of continuous and discrete time utilizing integer wavelet transform (IWT) that incorporates lifting scheme (LS) excellently. As compared to wavelet decomposition, here both approximation as well as detailed contents of the image under consideration are further decomposed, which enhances the compression ratio. Bi-orthogonal wavelets are constructed using LS that makes use of both high pass and low pass filter values along with addition and shift operations on the resulting wavelet coefficients quite suitably. Forward as well as inverse lifting schemes are implemented to reduce the computational complexity and achieve superior image compression performance 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 the domain of image compression and reconstruction that will immensely benefit the researchers and experimentalists involved with image and signal processing.