Performance Image Compression using Lifting based EEWITA
Assistant professor, Dept. of E&I, Bharath University, Chennai, India
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To enable wireless Internet and other data services using mobile appliances, there is a critical need to support content rich cellular data communication, including voice, text and image. However, mobile communication of multimedia content has several problem.It includes roundoff noise and bandwidth constraints of the wireless network.In this paper,I address the bandwidth and Roundoff Noise in the image data communication .I present energy efficient for still images,that can significantly minimize the energy required for wireless image communication, while meeting bandwidth constraints.Through lifting based DWT Roundoff noise is avoided.In lifting scheme, the output of the DWT is integer value,it is fixed point,so no round off error occur. Based on wavelet image compression, we propose an energy efficient wavelet image transform algorithm (EEWITA) for lossy compression of still images, enabling significant reductions in computation as well as communication energy by using H* Elimination. By using this method I can achieve high compression ratio and minimum energy in the wireless internet.