Video quality assessments represent useful tools not only to evaluate the quality of the received video, but also to enable unequal error protection mechanisms. The computational cost of these quality assessments is however a relevant limitation to their use, mainly in the presence of time constraints, such as in live streaming applications. This paper proposes an algorithm capable to estimate, with a very low computational cost, the distortion due to the loss of a frame on videos encoded using the H.264 Scalable Video Coding (SVC) standard, by adopting one of the most reliable video quality assessments: the Structural SIMilarity (SSIM) index. The results show that the proposed solution allows one to obtain a satisfactory approximation of the exact SSIM-based distortion, simultaneously reducing the time required by the estimation process. The approximated SSIM distortion values are finally applied to an 802.11e distributed network with energy constraints, in order to test the effectiveness of the conceived algorithm in a practical scenario.
