Wireless H.264 Video Quality Enhancement Through Optimal Prioritized Packet Fragmentation

Abstract

We introduce a cross-layer priority-aware packet fragmentation scheme at the MAC layer to enhance the quality of pre-encoded H.264/AVC compressed bitstreams over bit-rate limited error-prone links in wireless networks. The H.264 slices are classified in four priorities at the encoder based on their cumulative mean square error (CMSE) contribution towards the received video quality. The slices of a priority class in each frame are aggregated into video packets of corresponding priority. We derive the optimal fragment size for each priority class which achieves the maximum expected weighted goodput at different encoded video bit rates, slice sizes and bit error rates. Priority-aware packet fragmentation invokes slice discard in the buffer due to channel bit rate constraints on allocating fragment header bits. We propose a slice discard scheme using frame importance and slice CMSE contribution to control error propagation effects. Packet fragmentation is extended to slice fragmentation by modifying the conventional H.264 decoder to handle partial slice decoding. Priority-aware slice fragmentation combined with the proposed slice discard scheme provides considerable PSNR and VQM gains as compared to priority-agnostic fragmentation.

An adaptive unequal error protection based on motion energy of H.264/AVC video frames

“…In this method, division of a frame into slices consequently reduces the overall transmission rate and the effectiveness of video compression is degraded. Slices can be prioritized based on the contribution of distortion to the video quality [6]. Information about slice importance is signaled to the Media Access Control (MAC) layer in order to separate bitstreams into different packets.…”

Optimal MTU for realtime video broadcast with packet loss — A QoE perspective

“…It is imperative from equation (3), that the higher packet loss probability would favor the smaller frame size, but at the expense of additional overhead associated with the number of bytes attached to each header. Another interesting point often neglected in the simulated studies is the fact that the intermediate node's latency sharply increases due to the number of packet processed in a specific time interval [11].…”

“…A somewhat similar study related to work, employing a cross layer approach, is reported in [11], but the results are generated in a simulated environment. The focus of that paper is on prioritizing video slices based on the mean square error rate at VCL layer.…”

Optimized cross-layer forward error correction coding for H.264 AVC video transmission over wireless channels

“…H.264 slices can be prioritized based on their distortion contribution to the received video quality [9,[33][34][35][36][37]. In this paper, the total distortion of a slice loss is computed using the cumulative mean square error (CMSE), which takes into consideration the error propagation within the entire GOP [9,34]. Let the original uncompressed video frame at time t be f (t), the decoded frame without the slice loss bef (t), and the decoded frame with the slice loss bef (t).…”

“…Since computing the video PSNR requires decoding the video at the receiver, it is not feasible to use PSNR directly as the optimization metric due to its heavy computational complexity. The PSNR of a compressed video stream depends on several factors, including the video characteristics, bit rate, the percentage of lost slices, and their CMSE values [9,34]. Therefore, we define a function 'normalized F, ' denoted by F, which represents the weighted distortion contributed by the slice loss rates and their corresponding normalized CMSE values, as…”