Video quality assessment becomes increasingly important nowadays. Therefore, it is desirable to develop a visual quality metric that correlates well with human visual perception.
In previous projects in SIPL, a new technique for quality assessment has been developed, based on DCT sub-bands similarity (DSS). The new technique shows excellent results in comparison to subjective results. Its low complexity makes it highly suitable for a variety of live-streaming applications. Yet, some changes have to be made.
The main goal of this project is to build up a prototype of a video quality assessment system, based on network similar to the IDF network, while using the DSS method. At this part of the project, we implemented the algorithm in C, improving execution times and memory consumption.
We start from presenting the algorithm for pairs of reference and distorted images. Later, we’ll adjust it for videos as well.
In addition, we start by presenting the Full Reference approach (assuming that the whole reference image is available at the receiver side). After that, we’ll discuss the Reduced Reference approach (assuming that only a few features of the reference image are available at the receiver side). It is a more practical approach and we’ve used it in our implementation of the system.