Roberto Rinaldo

Image coding by block prediction of multiresolution subimages

The redundancy of the multiresolution representation has been clearly demonstrated in the case of fractal images, but it has not been fully recognized and exploited for general images. Fractal block coders have exploited the self-similarity among blocks in images. We devise an image coder in which the causal similarity among blocks of different subbands in a multiresolution decomposition of the image is exploited. In a pyramid subband decomposition, the image is decomposed into a set of subbands that are localized in scale, orientation, and space. The proposed coding scheme consists of predicting blocks in one subimage from blocks in lower resolution subbands with the same orientation. Although our prediction maps are of the same kind of those used in fractal block coders, which are based on an iterative mapping scheme, our coding technique does not impose any contractivity constraint on the block maps. This makes the decoding procedure very simple and allows a direct evaluation of the mean squared error (MSE) between the original and the reconstructed image at coding time. More importantly, we show that the subband pyramid acts as an automatic block classifier, thus making the block search simpler and the block matching more effective. These advantages are confirmed by the experimental results, which show that the performance of our scheme is superior for both visual quality and MSE to that obtainable with standard fractal block coders and also to that of other popular image coders such as JPEG.

Lossless compression of video using temporal information

In this paper, we consider the problem of lossless compression of video by taking into account temporal information. Video lossless compression is an interesting possibility in the line of production and contribution. We propose a compression technique which is based on motion compensation, optimal three-dimensional (3-D) linear prediction and context based Golomb-Rice entropy coding. The proposed technique is compared with 3-D extensions of the JPEG-LS standard for still image compression. A compression gain of about 0.8 bit/pel with respect to static JPEG-LS, applied on a frame-by-frame basis, is achievable at a reasonable computational complexity.

Polyphase spatial subsampling multiple description coding of video streams with H264

In this work, we propose a multiple description (MD) coding system for video streams. In particular, our scheme originates four descriptions from the spatially downsampled polyphase components of the original frames. Each description is compressed independently with the recent H264/AVC video coding standard, it is packetized and sent over an error prone network. In case of errors in one or more descriptions, appropriate concealing is applied at the receiver, before insertion of the corrected frames into the corresponding receiver frame buffers. We propose and compare different concealment solutions and a post processing stage to attenuate visual effects related to MD coding. We analyze the trade off between robustness to channel errors and coding efficiency, comparing the proposed technique with single description (SD) video coding with H264/AVC. Experimental results validate the effectiveness of the proposed scheme.

A multiresolution approach to spike detection in EEG

A technique is proposed for the automatic detection of spikes in electroencephalograms (EEG). A multiresolution approach and a non-linear energy operator are exploited. The signal on each EEG channel is decomposed into three subbands using a non-decimated wavelet transform. Each subband is analyzed by using a non-linear energy operator, in order to detect peaks. A decision rule detects the presence of spikes in the EEG, relying upon the energy of the three subbands. The effectiveness of the proposed technique was confirmed by analyzing both test signals and EEG layouts.

Efficient reconstruction from frame-based multiple descriptions

Redundant bases or frames are a promising technique for multiple description signal coding. Frames can provide sufficient redundancy for recovery in case of coefficient losses due, for instance, to packet transmission errors. In this paper, we consider the problem of dual frame computation in the context of finite impulse response (FIR) analysis and synthesis filterbanks. In particular, we propose an algorithm for dual frame computation which recovers the missing frame coefficients, followed by synthesis with the original filterbank. It is shown that the algorithm operates locally and allows for reduced complexity and low-delay reconstruction of the original signal. The case of excessive losses and incomplete bases is also considered. Experiments are provided to evaluate the algorithm performance and test its applicability in practical contexts.

Modeling of subband image data for buffer control

We develop an adaptive scheme for quantization of subband or transform coded frames in a typical video sequence coder. Using a generalized Gaussian model for the subband or transform coefficients, we present a procedure to determine the optimum dead-zone quantizer for a given entropy of the quantizer output symbols. We find that, at low bit rates, the dead-zone quantizer offers better performance than the uniform quantizer. The model is used to develop an adaptive procedure to update the quantizer parameters on the basis of the state of a channel buffer with constant output rate and variable input rate. We compare the accuracy of the generalized Gaussian model in predicting the actual bit rate to that achievable using the simpler and more common Laplacian model. Experimental results show that the generalized Gaussian model has superior performance than the Laplacian model, and that it can be effectively used in a practical scheme for buffer control.

Rate allocation for robust video streaming based on distributed video coding

This paper proposes an error resilient coding scheme that employs distributed video coding tools. A bitstream, produced by any standard motion-compensated predictive codec (MPEG-x, H.26x), is sent over an error-prone channel. In addition, a Wyner-Ziv encoded auxiliary bitstream is sent as redundant information to serve as a forward error correction code. At the decoder side, error concealed reconstructed frames are used as side information by the Wyner-Ziv decoder, and the corrected frame is used as a reference by future frames, thus reducing drift. We explicitly target the problem of rate allocation at the encoder side, by estimating the channel induced distortion in the transform domain. Rate adaptivity is achieved at the frame, subband and bitplane granularity. Experimental results conducted over a simulated error-prone channel reveal that the proposed scheme has comparable or better performance than a scheme where forward error correction codes are used. Moreover the proposed solution shows good performance when compared to a scheme that uses the intra-macroblock refresh procedure.

Real-Time Multiple Description Video Streaming over QoS-Based Wireless Networks

We consider the problem of robust video streaming over networks that support QoS differentiation, such as the 802.11e wireless network infrastructure. We consider the benefits obtained matching the H.264 data partitioning (DP) mode with such a QoS-based interface. We compare this solution with an innovative scheme which combines a multiple description (MD) coding framework with a QoS-based network. Results are reported using both a simple IID channel model and a more realistic wireless network, simulated using the OmNet++ network simulator.

Bounds on error amplification in oversampled filter banks for robust transmission

This paper analyzes the problem of error amplification in frame-based coding schemes derived from oversampled filter banks. Oversampled filter banks are currently being proposed for robust transmission applications, since added redundancy can be used for error recovery in case of losses. Error amplification is determined by the lower bound of the subframe resulting after losses. Theoretical expressions are derived to characterize such lower bound for different loss statistics. Criteria are derived that can be useful for the design of oversampled filter banks in various applications. The analysis and some application examples demonstrate that filter bank performance strongly depends on how the coefficients are organized into packets.

Comparison Between Multiple Description and Single Description Video Coding With Forward Error Correction

Video streaming over packet switched best-effort networks is a challenging topic, due to low latency, scalability and fault tolerance requirements. Many techniques can be used to deal with delay, loss and the time-varying nature of best-effort networks. In this paper we compare two techniques to improve the performance of video streaming, i.e., a multiple description (MD) scheme based on spatial polyphase downsampling, and a single description (SD) scheme where robustness to packet loss is increased using forward error correcting (FEC) codes. We consider both a single channel scenario and a multiple channel (or multi-path) scenario. We span a large set of channel conditions, to consider the high packet loss probabilities common in wireless communication systems. A H.264/AVC video coding standard with advanced error concealment capabilities is used. Experimental results show that MD can be competitive in practical scenarios with more flexibility and less complexity than the SD+FEC scheme