DVC based video codecs proposed in the literature generally include a reverse (feedback) channel between the encoder and the decoder. This channel is used to communicate the dynamic parity bit request messages from the decoder to the encoder resulting in an optimum dynamic variable rate control implementation. However it is observed that this dynamic feedback mechanism is a practical hindrance in a number of practical consumer electronics applications. In this paper we proposed a novel transform domain Unidirectional Distributed Video Codec (UDVC) without a feedback channel. First, all Wyner-Ziv frames are divided into rectangular macroblocks. A simple metric is used for each block to represent the correlations between the corresponding blocks in the adjacent key frame and the Wyner-Ziv frame. Based on the value of this metric, parity is allocated dynamically for each block. These parities are either stored for offline processing or transmitted to the DVC decoder for on line processing. Simulation results show that the proposed codec outperforms the existing UDVC solutions by a significant margin.

In this paper, we propose a rate control technique for H.264/AVC using subjective quality of video for off line video coding. We propose to use Video Quality Metric (VQM) with an evolution strategy algorithm, which is capable of identifying the best possible quantization parameters for each frame/macroblock to encode the video sequence such that it would maximize the subjective quality of the entire video sequence subjected to the target bit rate. Simulation results suggest that the proposed technique can improve the RD performance of the H.264/AVC codec significantly. With the proposed technique, up to 40% bit rate reduction can be achieved at the same video quality. Furthermore, results show that the proposed technique can improve the subjective quality of the encoded video significantly for video sequences especially with high motion.

Distributed Video Coding (DVC) is an emerging video coding paradigm that is characterized by a flexible architecture for designing very low cost video encoders. This feature could be very effectively utilized in a number of potential many-to-one type video coding applications. However, the compression efficiency of the latest DVC implementations still falls behind the state-of-the-art in conventional video coding technologies, namely H.264/AVC. In this paper, a novel non-linear quantization algorithm is proposed for DVC in order to improve the rate-distortion (RD) performance. The proposed solution is expected to exploit the dominant contribution to the picture quality from the relatively small coefficients when the high concentration of the coefficients near zero as evident when the residual input video signal for the Wyner-Ziv frames is considered in the transform domain. The performance of the proposed solution incorporating the non-linear quantizer is compared with the performance of an existing transform domain DVC solution that uses a linear quantizer. The simulation results show a consistently improved RD performance at all bitrates when different test video sequences with varying motion levels are considered.

Distributed video coding (DVC) technology has been considered to be capable of reducing the processing complexity of the encoder immensely, while majority of the computational overheads are taken over by the decoder. In the common DVC framework, the pictures are decoded using the Wyner-Ziv encoded bit stream received from the encoder and the side information estimated using previously decoded information. As a result, accuracy of the side information estimation is very critical in improving the coding efficiency. In this paper we propose a novel side information refinement technique for DVC using multiple side information streams and sequential motion compensation with luminance and chrominance information involving iterative fusion of parallel information streams. In the bit plane wise coding architecture, previously decoded higher order bit planes are incrementally used to perform the motion estimation jointly in luminance and chrominance spaces to estimate multiple redundant bit streams for iterative fusion to produce more improved side information for subsequent bit planes. Simulation results show significant objective quality gain can be achieved at the same bit rate by utilizing the proposed refinement algorithms.

Distributed Video Coding (DVC) is an emerging video coding approach, particularly attractive due to its flexibility to implement low complex encoders. This feature could be very effectively utilized in a number of video sensor based application scenarios. However, DVC is still in the process of development and currently available codec implementations are based on a number of hypothetical models and assumptions. In DVC, the effects of noise and fading on the compressed payload (parity bit stream) in real video communications and the resultant modified channel model scenario have not been discussed in literature. In this paper, a solution to the above problem in turbo coding based DVC is discussed incorporating a novel dual channel model for the maximum a-posteriori (MAP) algorithm for turbo decoding. The simulations for AWGN and wireless channels at different group of picture (GOP) sizes show that the proposed algorithm improves the rate distortion performance compared to the existing decoding algorithm. It also outperforms the H.264/AVC I-P-I-P codec (v10.1/baseline profile); particularly at low Signal to Noise Ratio (SNR) levels of the channel, thus enabling DVC as a viable and efficient option for video communications.