Error Resilience Video Streaming Technique Based on Hybrid Multiple Description Coding and Image Pyramid

Abstract

Recently, video streaming gained popularity due to a lot of live streaming platforms with better Quality of Experience (QoE). However, transmitting video data over networks facing critical challenges because of maintaining video quality. With the goal of ensuring error resilience video streaming, this research proposes a novel Hybrid Multiple Description Coding and Image Pyramid (HMDC-IP) algorithm to enhance video transmission performance under varying network conditions. The MDC technique splits the video into multiple independently decodable descriptions, providing video recovery in case of packet loss. Simultaneously, the Image Pyramid method creates multiple resolution layers, allowing for flexible reconstruction of the video when data is lost. Notably, if all channels are received, then there will be no loss. Besides, polyphase permuting & splitting are applied to rearrange and split the image data into different polyphase components. After splitting, the data undergoes coefficient splitting which separates the image coefficients to allow finer control over encoding. These coefficients are then processed with arithmetic encoding to a form of entropy coding that compresses the data efficiently. On the decoding side, the descriptions are received and processed in reverse order. The system starts with arithmetic decoding, coefficient merger, polyphase inverse permuting & residual merger, and finally, the image is up-sampled through the Image Pyramid to restore the original resolution. Performance evaluation is carried out by measuring key metrics such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Error Recovery Rate (ERR). The results demonstrate that the proposed HMDC-IP framework significantly improves video quality, minimizes packet loss impact, and enhances error resilience compared to traditional methods.