video coding

In recent years, video-based applications have increased. Therefore, researchers are trying to make video coding techniques more effective and efficient. So, several methods are proposed to improve the quality of video against the channel error. The aim of this article is increasing video quality at the receiver. Basis of the proposed method is as follows; in a fixed rate, channel coding rate increases and using it to increase channel error robustness. Channel encoder rate increases with increasing compression rate and decreasing source data. Since the motion estimator block is unable to minimize the variance of the information frames correctly; in this paper, the secondary estimator is proposed which is applied to the information and it causes to increase source compression rate. So the combination of wavelet and neural network with genetic algorithm are used in this secondary estimator. The secondary estimator significantly reduces the information frames variance. Thus, fewer bits are needed to send information. So in this method, channel encoder rate increases without increasing transmitted data for each frame and video frames could be more robustness against to channel error. To evaluate the proposed method, we have tested different source coding rates with several SNRs and compared the results by other methods

In recent years, different networks for information transmission have been emerged. Multimedia information like video take much storage volume. This high storage volume needs high bandwidth, high electrical and computational power to process and transmission of data, which is not possible in many networks. For example, wireless multimedia sensor networks that have constraints in their resources like memory, bandwidth and energy consumption can be mentioned. In this paper, a system for environment monitoring consisting of a transmitter network, a receiver network and a base station with a transcoder has been introduced. In the proposed method, compression has been achieved using transcoding. This method has resulted in increasing of compression along with keeping the video quality and reduction of calculation complexity in coder and decoder. The simulation results of this method have been compared to classic video compression methods and the superiority of the proposed method has been presented.