Adaptive and energy efficient wavelet image compression for mobile multimedia data services

– To enable wireless Internet and other data services using mobile appliances, there is a critical need to support contentrich cellular data communication, including voice, text, image and video. However, mobile communication of multimedia content has several bottlenecks, including limited bandwidth of cellular networks, channel noise, and battery constraints of the appliances. In this paper, we address the energy and bandwidth bottlenecks of image data communication. We present an energy efficient, adaptive data codec for still images that can significantly minimize the energy required for wireless image communication, while meeting bandwidth constraints of the wireless network, the image quality, and latency constraints of the wireless service. 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 needed, with minimal degradation in image quality. Additionally, we identify wavelet image compression parameters that can be used to effect trade-offs between the energy savings, quality of the image, and required communication bandwidth. We also present a dynamic configuration methodology that selects the optimal set of parameters to minimize energy under network, service, and appliance constraints. We demonstrate the significant energy and air time (service cost) savings possible by using the proposed energy efficient, adaptive image codec under different cellular access technologies.