We propose a new channel adaptive distributed video coding algorithm, which is adaptive to time-varying available bitrate and packet loss ratio. The proposed method controls the quantization parameter according to channel condition of especially error-prone mobile channel. Simulation shows that the proposed algorithm outperforms the conventional rate-control-only algorithm.

This letter proposes a method to retrieve the original image X out of multiple sets of SI (Side Information) in distributed video coding (DVC). Using Turbo decoding methods, the most reliable segments from the decoded Yi's were selected for the composition of Y∞, whose conditional entropy H(X| Y∞) became much lower than any individual conditional entropy H(X| Yi). This proposal has improved the peak signal-to-noise ratio (PSNR) by 1.1 to 1.8 dB, compared to the conventional single SI-based approach.

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.

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.

We propose a new approach to personal identification using derived vectorcardiogram (dVCG). The dVCG was calculated from recorded ECG using inverse Dower transform. Twenty-one features were extracted from the resulting dVCG. To analyze the effect of each feature and to improve efficiency while maintaining the performance, we performed feature selection using the Relief-F algorithm using these 21 features. Each set of the eight highest ranked features and all 21 features were used in SVM learning and in tests, respectively. The classification accuracy using the entire feature set was 99.53 %. However, using only the eight highest ranked features, the classification accuracy was 99.07 %, indicating only a 0.46 % decrease in accuracy compared with the accuracy achieved using the entire feature set. Using only the eight highest ranked features, the conventional ECG method resulted in a 93 % recognition rate, whereas our method achieved >99 % recognition rate, over 6 % higher than the conventional ECG method. Our experiments show that it is possible to perform a personal identification using only eight features extracted from the dVCG.

A new current-mode quadrature oscillator circuit using two differential voltage current conveyors (DVCCs), two grounded capacitors and two grounded resistors is presented. Two high output impedance sinusoid current sources with 90phase difference are available in the proposed circuit. The oscillation condition and oscillation frequency are orthogonally controllable. The use of only grounded capacitors and resistors makes the proposed circuit ideal for integrated circuit implementation. Simulation results are also included.