Reduced-Reference Image Quality Assessment Based on Edge Preservation

Assessing the subjective quality of processed images through an objective quality metric is a key issue in multimedia processing and transmission. In some scenarios, it is also important to evaluate the quality of the received images with minimal reference to the transmitted ones. For instance, for closed-loop optimisation of image and video transmission, the quality measure can be evaluated at the receiver and provided as feedback information to the system controller. The original images - prior to compression and transmission - are not usually available at the receiver side, and it is important to rely at the receiver side on an objective quality metric that does not need reference or needs minimal reference to the original images. The observation that the human eye is very sensitive to edge and contour information of an image underpins the proposal of our reduced reference (RR) quality metric, which compares edge information between the distorted and the original image. Results highlight that the metric correlates well with subjective observations, also in comparison with commonly used full-reference metrics and with a state-of-the-art reduced reference metric. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

A Comparative Study of a Low Doppler Shift in a Carrier Tracking Loop for GPS

This paper compares a carrier tracking scenario when a received Global Positioning System (GPS) signal has low Doppler frequency. It is shown that if the Numerically Controlled Oscillator (NCO) is quantized to 1 bit, the carrier tracking loop is unable to keep track of the incoming signal which leaves the tracking loop oscillating between the upper and lower bounds of the tracking loop bandwidth. One way of overcoming this problem is presented and compared with another existing solution, found in the literature, providing comparative results from the use of real-recorded off the air GPS L1 signals. Results show that the proposed method performs better tracking performance compared with the existing solution which it requires much less hardware complexity.