Roya Choupani

Multiple description coding for SNR scalable video transmission over unreliable networks

Streaming multimedia data on best-effort networks such as the Internet requires measures against bandwidth fluctuations and frame loss. Multiple Description Coding (MDC) methods are used to overcome the jitter and delay problems arising from frame losses by making the transmitted data more error resilient. Meanwhile, varying characteristics of receiving devices require adaptation of video data. Data transmission in multiple descriptions provides the feasibility of receiving it partially and hence having a scalable and adaptive video. In this paper, a new method based on integrating MDC and signal-to-noise ratio (SNR) scalable video coding algorithms is proposed. Our method introduces a transform on data to permit transmitting them using independent descriptions. Our results indicate that on average 1.71dB reduction in terms of Y-PSNR occurs if only one description is received.

Multiple Description Scalable Coding for Video Transmission over Unreliable Networks

Developing real time multimedia applications for best effort networks such as the Internet requires prohibitions against jitter delay and frame loss. This problem is further complicated in wireless networks as the rate of frame corruption or loss is higher in wireless networks while they generally have lower data rates compared to wired networks. On the other hand, variations of the bandwidth and the receiving device characteristics require data rate adaptation capability of the coding method. Multiple Description Coding (MDC) methods are used to solve the jitter delay and frame loss problems by making the transmitted data more error resilient, however, this results in reduced data rate because of the added overhead. MDC methods do not address the bandwidth variation and receiver characteristics differences. In this paper a new method based on integrating MDC and the scalable video coding extension of H.264 standard is proposed. Our method can handle both jitter delay and frame loss, and data rate adaptation problems. Our method utilizes motion compensating scheme and, therefore, is compatible with the current video coding standards such as MPEG-4 and H.264. Based on the simulated network conditions, our method shows promising results and we have achieved up to 36dB for average Y-PSNR.

A Drift-Reduced Hierarchical Wavelet Coding Scheme for Scalable Video Transmissions

Scalable video coding allows for the capability of (partially) decoding a video bitstream when faced with communication deficiencies such as low bandwidth or loss of data resulting in lower video quality. As the encoding is usually based on perfectly reconstructed frames, such deficiencies result in differently decoded frames at the decoder than the ones used in the encoder and, therefore, leading to errors being accumulated in the decoder. This is commonly referred to as the drift error. Drift-free scalable video coding methods also suffer from the low performance problem as they do not combine the residue encoding scheme of the current standards such as MPEG-4 and H.264 with scalability characteristics. We propose a scalable video coding method which is based on the motion compensation and residue encoding methods found in current video standards combined with the scalability property of discrete wavelet transform. Our proposed method aims to reduce the drift error while preserving the compression efficiency. Our results show that the drift error has been greatly reduced when a hierarchical structure for frame encoding is introduced.

Unbalanced multiple description wavelet coding for scalable video transmission

Abstract. Scalable video coding and multiple description coding are the two different adaptation schemes for video transmission over heterogeneous and best-effort networks such as the Internet. We propose a new method to encode video for unreliable networks with rate adaptation capability. Our proposed method groups three dimensional discrete wavelet transform coefficients in different descriptions and applies a modified embedded zero tree data for rate adaptation. The proposed method optimizes the bit-rates of the descriptions with respect to the channel bit rates and the maximum acceptable distortion. The experimental results in the presence of one description loss indicate that on average the videos at the rate of 1000  Kbit/s are reconstructed with Y-component of peak signal to noise ratio (Y-PSNR) value of 36.2 dB. The dynamic allocation of descriptions to the network channels is optimized for rate distortion minimization. The improvement in term of Y-PSNR achieved by rate distortion optimization has been between 0.7 and 5.3 dB in different bit rates.

Drift-free video coding for privacy protected video scrambling

With video surveillance systems becoming ubiquitous nowadays, protecting peoples privacy raises an increasingly serious concern. Video streaming with privacy protection requires modifying parts of the video content. This modification should provide the possibility of unprotected access to the video if the user is authenticated through a private key. However, any modification in the content of a video can result in a drift error and deteriorate the quality of the reconstructed video. In addition, it is required that the privacy protection does not adversely affect the computational complexity and the coding efficiency in terms of bitrate. In this work, we propose a drift-free method for scrambling the privacy protected regions of the frames while preserving the coding efficiency. Our proposed method provides the possibility of utilizing private keys for restricting unauthorized access to the private contents of the video with a small increase in the computational complexity of the encoder and decoder. The experimental results indicate that our proposed drift-free method can achieve a higher coding efficiency of 0.6 dB on average compared to similar methods.

Using wavelet transform self-similarity for effective multiple description video coding

Video streaming over unreliable networks requires preventive measures to avoid quality deterioration in the presence of packet losses. However, these measures result in redundancy in the transmitted data which is utilized to estimate the missing packets lost in the delivered portions. In this paper, we have used the self-similarity property if the discrete wavelet transform (DWT) to minimize the redundancy and improve the fidelity of the delivered video streams in presence of data loss. Our proposed method decomposes the video into multiple descriptions after applying the DWT. The descriptions are organized in such a way that when one of them is lost during transmission, it is estimated using the delivered portions by means of self-similarity between the DWT coefficients. In our experiments, we compare video reconstruction in the presence of data loss in one or two descriptions. Based on the experimental results, we have ascertained that our estimation method for missing coefficients by means of self-similarity is able to improve the video quality by 2.14dB and 7.26dB in case of one description and two descriptions, respectively. Moreover, our proposed method outperforms the state-of-the-art Forward Error Correction (FEC) method in case of higher bit-rates.

Hierarchical SNR Scalable Video Coding with Adaptive Quantization for Reduced Drift Error

In video coding, dependencies between frames are being exploited to achieve compression by only coding the differences. This dependency can potentially lead to decoding inaccuracies when there is a communication error, or a deliberate quality reduction due to reduced network or receiver capabilities. The dependency can start at the reference frame and progress through a chain of dependent frames within a group of pictures (GOP) resulting in the so-called drift error. Scalable video coding schemes should deal with such drift errors while maximizing the delivered video quality. In this paper, we present a multi-layer hierarchical structure for scalable video coding capable of reducing the drift error. Moreover, we propose an optimization to adaptively determine the quantization step size for the base and enhancement layers. In addition, we address the trade-off between the drift error and the coding efficiency. The improvements in terms of average PSNR values when one frame in a GOP is lost are 3.70(dB) when only the base layer is delivered, and 4.78(dB) when both the base and the enhancement layers are delivered. The improvements in presence of burst errors are 3.52(dB) when only the base layer is delivered, and 4.50(dB) when both base and enhancement layers are delivered.

Spatial Multiple Description Coding for Scalable Video Streams

The need for adapting video stream delivery over heterogeneous and unreliable networks requires self-adaptive and error resilient coding. Network bandwidth fluctuations can be handled by means of a video coding scheme which adapts to the channel conditions. However, packet losses which are frequent in wireless networks can cause a mismatch during the reconstruction in the receiver end and result in an accumulation of errors which deteriorates the quality of the delivered video. A combination of multiple description coding in pixel domain and scalable video coding schemes which addresses both video adaptation and robustness to data loss is proposed in this paper. The proposed scheme combines error concealment with spatial video scalability. In order to improve the fidelity of the reconstructed to the original frames in presence of packet loss, a multilayer polyphase spatial decomposition algorithmis proposed. Classical multiple description methods interpolate themissing data which results in smoothing and artifact at object boundaries. The proposed algorithm addresses the quality degradation due to low-pass filtering effect of interpolation methods.We also comparatively analyze the trade-off between robustness to channel errors and coding efficiency.

Optimized Multiple Description Coding for Temporal Video Scalability

The vast application of video streaming over the Internet requires video adaptation to the fluctuations of the available bandwidth, and the rendering capabilities of the receiver device. On the other hand, the available video coding standards are designed for optimum bit rate which makes them susceptible to packet losses. A combination of video adaptation methods and error resilient methods can make the video stream more robust against networking problems. In this paper, an optimization for combining scalable video coding with multiple description coding schemes have been proposed. Our proposed method is capable of creating balanced descriptions with optimum coding efficiency.