Quality Enhancement of Synthesized Video by Improvement of VLC Using Artificial Neural Network

Hassan Farsi,Pouriya Etezadifar

doi:10.19026/rjaset.6.3611

Hassan Farsi, Pouriya Etezadifar

Open Access

https://doi.org/10.19026/rjaset.6.3611

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Abstract

Progress of technology in recent decade's causes that video transmission via communication channels has met high demands. Therefore, several methods have been proposed to improve the quality of video under channel errors. The aim of this study is to increase PSNR for synthesized video by increasing channel encoder rate but in constant transmission rate. This is achieved by using intelligent neural network and Huffman coding in VLC blocks used in the MPEG standard to compress transmitted data significantly. Then, depending to the amount of compression by the proposed method, the compressed data is coded again using secondary channel encoder. The proposed method is able to increase channel coding rate without increasing the amount of information for each frame. This method provides more robustness for video frames against channel errors. The proposed method is tested for different source coding rates and several SNRs for channel and the obtained results are compared with a new method named Farooq method.

Highlights

Todays, increasing grow of using wireless channels and mobile telecommunication and tend to serve the achievements of modern telecommunications for realtime multimedia data transmission such as video involves advance research in this area (Flierl and Girod, 2004)
We propose a new method to estimate and send Probability Density Function (PDF) based on the Huffman code and we use neural network to memorize transmitted bit stream for increasing the compression after passing through the Variable Length Coding (VLC) block
The number of Foreman video frames is 123 that 3 frames are coded as I-picture and the rest frames are divided into three parts

Summary

Introduction

Todays, increasing grow of using wireless channels and mobile telecommunication and tend to serve the achievements of modern telecommunications for realtime multimedia data transmission such as video involves advance research in this area (Flierl and Girod, 2004). Different methods as combination of channel and source coding have been introduced. JSCC is generally based on channel estimation (Bystrom and Modestino, 2000; Cheung and Zakhor, 2000; Kondi et al, 2002; Zhai et al, 2006). This means that in order to have higher PSNR, higher channel coding rate is required. The proposed method is able to be applied on every source coding rate, independently and to improve the quality of the reconstructed video frames at receiver. Peak Signal to Noise Ratio (PSNR) and Bit Error Rate (BER) are used as metrics measures to indicate the quality of the reconstructed video

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Results

Conclusion