Bit Rate Control for Video Transmission Over Wireless Networks

Indian Journal of Science and Technology, Vol 9(S), DOI: 0.75/ijst/06/v9iS/05, December 06 ISSN (Print) : 097-686 ISSN (Online) : 097-5 Bit Rate Control for Video Transmission Over Wireless Networks K. Srinivasa Rao * and K. Sri Rama Krishna JNTUH, Hyderabad - 500085, Telangana, India; ksrphdrao@gmail.com VR Siddhartha Engineering College, Vijayawada - 50007, Andhra Pradesh, India Abstract This paper developed a model of bit- rate control for video streaming over constant bit-rate communication channel, where the MPEG-, standard Variable Bit-Rate (VBR), is adapted to be used as a Constant Bit Rate (CBR). The targeted image quality is based on the buffer level controlling on the output rate of the video encoder. A CBR transport over networks, result is better performing than that of VBR. It provided flexibility to monitor network and to analyse, where the VBR video streaming over CBR channel can be chosen to remove the problem of congestion. This paper makes the study about the basic problem of adapted VBR-compress the video for transport over a CBR channel. The improved systems are carried using Matlab (Ver 6.5) under Windows XP operating system. Keywords: Constant Bit Rate, Multiple-Input Multiple-Output(MIMO), Rate-Distortion, Video Streaming, Variable Bit Rate. Introduction Multiple-Input Multiple-Output (MIMO) is an antenna technology for wireless communications, used for more data transfer at the same time with the use of the multiple transmitters and receivers. Multipath known as MIMO technology take the benefit reflected signals to provide gains in channel robustness and throughput. Figure. MIMO technology uses multiple radios to transfer more data at the same time. MIMO technology utilizes multipath behavior by using multiple, smart antennas at transmitters and receivers with an improved spatial dimension to highly improve the range and performance. At the same time, it uses multiple antennas to receive and send multiple spatial streams which will make antennas to work smarter than by keeping them to combine data streams coming from multiple directions and at different times to highly increase the signal power at the receiver. Smarter antennas use spatial diversity technique for better use of surplus antennas. If there is more number of antennas than spatial streams, then the extra antennas can add to receiver diversity and increases its range. In SIMO as two forms can be given as: Switched Diversity SIMO: This form of SIMO checks for the strongest signal and connects to that antenna. Maximum ratio combining SIMO: This type of SIMO takes the two signals to give a resultant of the two signals. Thererefore the signals from the two antennas will contribute to provide an overall signal. It has two main designs for MIMOs are given below: Spatial diversity: It indicates to that transmit and receive diversity uses the spatial diversity. These two methods are to improve the signal to *Author for correspondence

Bit Rate Control for Video Transmission Over Wireless Networks noise ratio and performance of the system due to the different types of fading. Spatial multiplexing: This type of MIMO achieves extra data capacity by using the multiple paths to move additional data. Favors of MIMO Technology To eliminate the bad effects due to multi-path and fading, the multiple antenna configurations are used to get high data throughput. Better Data Rates, Better Transmission Quality (BER) and Reliability.. Existing System We addressed the problem of efficient bit allocation of a fixated in coding the optimal bit allotment of independently coded signal blocks have been studied in the blurb. These techniques extended to the more general temporally and spatially dependent coding methods, of particular choices are the typical MPEG video coder and multiresolution coders. This approach utilizes a Rate- Distortion (RD) framework for arbitrary quantizer sets.. Proposed System This paper is aimed at a method of bit-rate control for video streaming over constant bit-rate communication channel, where the MPEG- standard Variable Bit-Rate (VBR), is adapted to be utilized as a Constant Bit Rate (CBR). Feedback based on the buffer level controls the target image quality and rate of output of the video encoder. A CBR transport over networks, result is a better performance than that of VBR. These rate control schemes generally solve two important problems. Firstly it is how to allocate the required bits to each coding unit based on the buffer status, i.e., rate allocation, and the secondly it is how to adjust the encoder parameters to encode correctly each unit with the allocated bits i.e., quantization parameter adjustment. The calculation of PSNR is easy and gives a rough approximate to the visual quality of the video frame. A high PSNR shows a high-quality frame.. The Advantages of the Proposed System These rate-control schemes are generally are aimed at to solve mainly two problems. Firstly is rate allocation and the secondly is quantization, parameter adjustment. High PSNR.. Video Compression Video compression, which is a necessary process for video communication over networks, removes spatial and temporal redundancies contained in video sequences. The decrease in distortion gives rise to an increase in rate and the increase in distortion gives rise to decrease in rate. So the basic problem in rate control can be stated that min D, s. t. R R max Where Rmax indicates the highest bit rate. Alternately, rate control is to get the highest picture quality (minimum distortion) without crossing the highest allowed bit rate. The Peak Signal to Noise Ratio (PSNR) represents the quality. Raw video should be compressed before transmission because to achieve efficiency. Video compression schemes are classified into two methods: scalable and non-scalable video coding. Because scalable video is capable of fitly coping with the bandwidth fluctuations in the Internet. Scalable video coding techniques have capacity to reconstruct lower quality frames. The requirements imposed by streaming applications on the video encoder and decoder can also be discussed. Figure. Nonscalable video encoder. Figure. Nonscalable video decoder. Vol 9 (S) December 06 www.indjst.org Indian Journal of Science and Technology

K. Srinivasa Rao and K. Sri Rama Krishna 5. Rate Control Constrained Quality Rate control always adjusts encoder parameters dynamically to get targeted bitrate probems in practical applications. A buffer is kept after the video encoder and before the transmission channel to make smooth the variation of the rate since the amount of information in compressed video sequences is apparently variable. A buffer is kept after the video encoder and before the transmission channel to mitigate the rate variation. The proposed rate control algorithm is aimed for bit-rate control includes the requirements of MPEG- video coding standard. The TM5 rate control algorithm is designed for bit-rate control in MPEG- video coding method. It consists of the following steps: Target bit allocation: The picture- type and universal weighting factors will form the basis for the Target number of bits for the next picture Rate control: The reference value of the QP for each Macro Block (MB) (Qj) is fixed as below: Q j =(B j *)/r Where r = R/f, R indicates the bit rate (bps), f denotes the frame rate (fps), for a constant quantization step size of, and Bj is the completeness of of the buffer. Adaptive quantization:, The QP for MB j is mquantj = Qj N_actj and is clipped to the range, where N_actj is the normalized spatial activity measure for the MB j. 5. Mode and Size Selection In video coding, there are distinct frame types I, P, and B frames with varieties of Macro Block (MB) units. 6. Frame Dropping Filter: Rate Shaping The frame dropping filter is for to decrease the data rate of a video stream by removing a number of frames depending on their relative preference and transmitting the remaining frames which also leads to improved video quality. Before removing the temporal redundancy from the current Inter-frame, it is compared with the previous Figure. The frame dropping sequence. Vol 9 (S) December 06 www.indjst.org Indian Journal of Science and Technology

Bit Rate Control for Video Transmission Over Wireless Networks frame and the difference is measured between them. If the difference is very small, the current frame will be removed, and the next frame is utilized as the current frame. But in the receiver side, the dropped frame will be displayed by repeating the previous frame, (i.e., if we transmit 0 frame per second (fps), and for example in the encoder side, two frames are discarded, then in the receiver side the number of frames that will be displayed are frames, because the system was designed to transmit 0 fps). But if there are no frames to be discarded, then the number of frames displayed equal to the number of frames transmitted. The procedure of frame dropping is as follows: Step : Estimate the similarity between the frames. Step : If the current frame is very similar to the pervious frame, then it s drop. Step : The step and repeated for all frame in video sequence. The encoder transmits the coded frame with its number and it would be utilized in decoder side to find the dropped frame. Fig. of The frame dropping sequence shows the frame dropping sequence. image quality considered as the Peak Signal-To- Noise Ratio (PSNR), which can be given as: n ( ) PSNR( db) = 0log0 MSN Where n is the number of bits per image sample and MSE is the Mean Squared Error between the distorted frame and the original frame. H W MSE = ((,) I r c W H r= 0 c= 0 I^ ( rc, )) This ratio represents the size of the original uncompressed video to the size of compressed video. 7. Basic Unit Bit Allocation The «Basic Unit of this scheme, rate control may be done to different levels of granularity, such as picture, slice, MB row or any consecutive group of MBs. That level is taken as a basic unit» at which rate control is resolved, and for which different values of QPs are calculated. 8. Motion Estimation and Compensation For the video sequence which is not compressed, input is subjected to temporal redundancy reduction by considering resemblances among adjoining video frames. Temporal redundancy is evolved due to the differences between two consecutive frames are generally similar mainly for large frame rates, because the objects in the scene can only have small displacements. The change between consecutive frames can be made smaller by using motion estimation because they are more resemblant. Compression can be obtained by guessing the successive frame when compared to the original frame. The performance of the proposed compression system was evaluated by taking a good quantitative parameter of Figure 5. Block diagram of the proposed system. In this paper the constant compression ratio is maintained whatever our varying like GOP and Quality. Bit rate changes when Quality changes, and then the change of PSNR is only when GOP (group of pixel) changes. For example: see table in this. GOP is equal to 60, quality (90, 70, 50, 0 and 0), corresponding bit rates (0.09, 0.0, 0.057, 0.08 and 0.66), PSNR is 8... GOP is change then PSNR also change, in this GOP is 0 then PSNR is. Vol 9 (S) December 06 www.indjst.org Indian Journal of Science and Technology

K. Srinivasa Rao and K. Sri Rama Krishna Table. GO P Quali ty Bit rate CR PSN R Encoding Time Decoding Time 90 0.0 9 8. 67.55 5 5.5 70 0.0 8. 69.9 57.05 50 0.05 7 8. 66.88 5.8 9 60 0 0 0.08 0.6 6 90 0.0 9 8. 8. 80.00 67.975 9.90 5.750 55.905 8. Figure 6. Original frame. 70 0.0 96.860.7 50 0.05 7 89.5 7 8.8 0 0 0 0 0.08 0.6 6 97.7 9.65 6 8. 9 85.8 90 0.0 9 9.90 8. 70 0.0 96.860.7 Figure 7. Deviation extracted frame. 0 50 0.05 7 0 0.08 89.5 7 97.7 8.8 0 8. 9 0 0.6 6 9.65 6 85.8 90 0.0 9 86. 6. 0 87.65 70 0.0 86. 5.78 7 00.0 0 50 0.05 7 86. 0. 97 98.7 0 0 0.08 86. 59.85 6.59 7 But in this GOP the decrease in PSNR will increase and in the GOP quality decreases Bit rate increases. Encoding and decoding time based on processor time. Figure 8. Labeled frame. Vol 9 (S) December 06 www.indjst.org Indian Journal of Science and Technology 5

Bit Rate Control for Video Transmission Over Wireless Networks We can see Figure 6 it is which frame you taken, Figure 7 shows how deviate the original frame and Figure 8 is a labeled frame this is which object you want detected. But in this paper main advantage is you re increasing GOP frames up to 60 no data will loss, the compression of any frame is in * pixel ranges only. We can observed graphs also see Figure 9. Quality versus compression Ratio. And also see Figure 0. Quality versus Bit rate and PSNR 9. Conclusion In this we have to observe GOP on video, in this GOP the increase will decrease PSNR and bit rate maintained,in the GOP we take some Qualities (90,70,50,0,0) in this bit rate is constant it is main advantage. 0. Future Scope In this we have developed up to 60 GOP without data losses, improve more GOP without data losses in real time.. References Figure 9. Quality vs. compression ratio.. Chen Z, Ngan KN. Recent advances in rate control for video coding, Signal Processing: Image Communication. 007; ():9 8.. Ortega A. Variable bit-rate video coding. Sun M-T, Reibman AR, editors. Compressed Video over Networks. New York, NY: Marcel Dekker,; 000. p. 8.. Ortega A, Ramchandran K. Ratedistortion methods for image and video compression. IEEE Signal Process. 8; 50.. Lee J, Dickinson BW. Rate-distortion optimized frame type selection for MPEG encoding. IEEE Trans Circuits Systems Video Technol. 7; 7:50 0. 5. Wu D, Hou YT, Zhu W, Zhang Y, Peha JM. Streaming Video over the Internet: Approaches and directions. IEEE Transactions on Circuits and Systems for Video Technology. 00; ():8 00. 6. Yu H, Lin Z, Pan F. Applications and improvement of H.6 in medical video compression. IEEE Transactions on Circuits and Systems-I. 005; 5():005. 7. Sullivan G, Wiegand T, Lim KP. Joint model reference encoding methods and decoding concealment method. JVTI09. San Diego; 00 Sep. 8. Ho. Variable block size motion estimation hardware for video encoders [MPhil thesis]. Hong Kong: The Chinese University of Hong Kong; 006 Nov. Figure 0. Quality vs bitrate and PSNR. 6 Vol 9 (S) December 06 www.indjst.org Indian Journal of Science and Technology