In the context of the RESUME-project a scalable wavelet-based video decoder was built to demonstrate the benefits of reconfigurable hardware for scalable applications. emph{Scalable} video means that the quality of service (QoS), i.e., the frame rate, resolution, color depth, ldots of the decoded video can easily be changed by only decoding those parts of the video stream that contribute to the desired QoS. With the emergence of high-performance FPGAs (Field Programmable Gate Array), both the required performance for real-time decoding and flexibility, by allowing reconfiguration, are offered. Since the amount of calculations scales with the QoS, energy dissipation is expected to scale similarly. To investigate the relation between QoS and energy dissipation we actually measured the energy dissipation of a scalable video decoder implementation on a FPGA. The measurements show how dissipation effectively scales with the QoS, but also depends on the decoded data and the used design method. This is illustrated by comparing two different implementations of the inverse discrete wavelet transform (IDWT).