Ralph Neff

Very low bit-rate video coding based on matching pursuits

We present a video compression algorithm which performs well on generic sequences at very low bit rates. This algorithm was the basis for a submission to the November 1995 MPEG-4 subjective tests. The main novelty of the algorithm is a matching-pursuit based motion residual coder. The method uses an inner-product search to decompose motion residual signals on an overcomplete dictionary of separable Gabor functions. This coding strategy allows residual bits to be concentrated in the areas where they are needed most, providing detailed reconstructions without block artifacts. Coding results from the MPEG-4 Class A compression sequences are presented and compared to H.263. We demonstrate that the matching pursuit system outperforms the H.263 standard in both peak signal-to-noise ratio (PSNR) and visual quality.

Video compression using matching pursuits

The use of matching pursuit (MP) to code video using overcomplete Gabor basis functions has recently been introduced. In this paper, we propose new functionalities such as SNR scalability and arbitrary shape coding for video coding based on matching pursuit. We improve the performance of the baseline algorithm presented earlier by proposing a new search and a new position coding technique. The resulting algorithm is compared to the earlier one and to DCT-based coding.

Matching pursuit video coding .I. Dictionary approximation

We have shown in previous works that overcomplete signal decomposition using matching pursuits is an efficient technique for coding motion-residual images in a hybrid video coder. Others have shown that alternate basis sets may improve the coding efficiency or reduce the encoder complexity. In this work, we introduce for the first time a design methodology which incorporates both coding efficiency and complexity in a systematic way. The key to the method is an algorithm which takes an arbitrary 2-D dictionary and generates approximations of the dictionary which have fast two-stage implementations according to the method of Redmill et al. (see Proc. IEEE Int. Conf. Image Processing, p.769-773, 1998). By varying the quality of the approximation, we can explore a systematic tradeoff between the coding efficiency and complexity of the resulting matching pursuit video encoder. As a practical result, we show that complexity reduction factors of up to 1000 are achievable with negligible coding efficiency losses of about 0.1-dB PSNR.

Modulus quantization for matching-pursuit video coding

Overcomplete signal decomposition using matching pursuits has been shown to be an efficient technique for coding motion-residual images in a hybrid video coder. Unlike orthogonal decomposition, matching pursuit uses an in-the-loop modulus quantizer which must be specified before coding begins. This complicates the quantizer design, since the optimal quantizer depends on the statistics of the matching-pursuit coefficients which in turn depend on the in loop quantizer actually used. In this paper, we address the modulus quantizer design issue, specifically developing frame-adaptive quantization schemes for the matching-pursuit video coder. Adaptive dead-zone subtraction is shown to reduce the information content of the modulus source, and a uniform threshhold quantizer is shown to be optimal for the resulting source. Practical two-pass and one-pass algorithms are developed to jointly determine the quantizer parameters and the number of coded basis functions in order to minimize coding distortion for a given rate. The compromise one-pass scheme performs nearly as well as the full two-pass algorithm, but with the same complexity as a fixed-quantizer design. The adaptive schemes are shown to outperform the fixed quantizer used in earlier works, especially at high bit rates, where the gain is as high as 1.7 dB.

Matching pursuit video coding at very low bit rates

Matching pursuits refers to a greedy algorithm which matches structures in a signal to a large dictionary of functions. In this paper, we present a matching-pursuit based video coding system which codes motion residual images using a large dictionary of Gabor functions. One feature of our system is that bits are assigned progressively to the highest-energy areas in the motion residual image. The large dictionary size is another advantage, since it allows structures in the motion residual to be represented using few significant coefficients. Experimental results compare the performance of the matching-pursuit system to a hybrid-DCT system at various bit rates between 6 and 128 kbit/s. Additional experiments show how the matching pursuit system performs if the Gabor dictionary is replaced by an 8/spl times/8 DCT dictionary.

Very low bit-rate video coding using matching pursuits

The term matching pursuits refers to a greedy algorithm which matches signal structures to a large, diverse dictionary of functions. The technique was proposed by Mallat and Zhang with an application to signal analysis. In this paper, we show how matching pursuits can be used to effectively code the motion residual in a hybrid video coding system at bit rates below 20 kbit/s. One advantage of this technique at low bit rates is that bits are assigned progressively to high energy areas in the motion residual. The proper choice of a dictionary set can lead to other advantages. For instance, a large dictionary with a wide variety of structures can represent a residual signal using fewer coefficients than the DCT basis. Also, a dictionary which is not block-based can reduce block distortions common to low bit rate DCT systems. Experimental results are presented in which the DCT residual coder from a standard coding system is replaced by a matching pursuit coder. These results show a substantial improvement in both PSNR and perceived visual quality. Further improvements result when the matching pursuit coder is paired with a smooth motion model using overlapping motion blocks.

Decoder complexity and performance comparison of matching pursuit and DCT-based MPEG-4 video codecs

Matching pursuits is an overcomplete expansion technique which has been successfully applied to the problem of coding motion residual images in a hybrid video coder. In this paper, the coding efficiency and decoder complexity of the method are compared to that of the DCT-based MPEG-4 standard with and without post-processing. Without post-processing, matching pursuits is shown to have significantly better PSNR and visual quality and similar decoding complexity compared to the MPEG-4 DCT decoder. To achieve reasonable quality at low bit rates, the DCT-based scheme requires post-processing, while the patching pursuit scheme does not. We show that the MPEG-4 post-processing filters have a prohibitive cost, increasing decoder complexity by a factor of 3 to 8. Finally, we introduce an all-integer matching pursuit implementation. The performance is shown to be within 0.05 dB of the original floating point algorithm.

Matching-pursuit video coding .II. Operational models for rate and distortion

For pt. I see ibid., vol.12 , no.1, (2000).We introduce two models for predicting the rate and distortion of the matching-pursuit video codec. The first model is based on a pre-coding analysis pass using the full matching-pursuit dictionary. The second model is based on a reduced-complexity analysis pass. We evaluate these models for use within existing rate-distortion optimization techniques. Our prediction results suggest that the models have sufficient accuracy to be useful in this context, and that significant complexity reductions could be achieved compared to exact rate-distortion computation.

Dictionary approximation for matching pursuit video coding

Previously, we demonstrated an efficient video codec based on overcomplete signal decomposition using matching pursuits. Dictionary design is an important issue for this system, and others have shown alternate dictionaries which lead to either coding efficiency improvements or reduced encoder complexity. We introduce for the first time a design methodology which incorporates both coding efficiency and complexity in a systematic way. The key to our new method is an algorithm which takes an arbitrary 2-D dictionary and generates approximations of the dictionary which have fast 2-stage implementations. By varying the quality of the approximation, we can explore a systematic tradeoff between the coding efficiency and complexity of the matching pursuit video encoder. As a practical result, we show cases where complexity is reduced by a factor of 500 to 1000 in exchange for small coding efficiency losses of around 0.1 dB PSNR.

Adaptive modulus quantizer design for matching pursuit video coding

Overcomplete signal decomposition using matching pursuits has been shown to be an efficient technique for coding motion residual images in a hybrid video coder. Unlike orthogonal decomposition where computation of the transform coefficients is decoupled from quantization, matching pursuit uses an in-loop quantizer which must be specified before coding begins. Optimal quantizer design thus depends on the computed matching pursuit coefficients, but these in turn depend on the chosen quantizer. To resolve this interdependency, we propose frame-adaptive quantization for matching pursuit based on adaptive dead-zone subtraction followed by uniform threshold quantization. Practical 2-pass and 1-pass algorithms are developed which jointly find the quantizer parameters and the number of coded basis functions which minimize coding distortion for a given rate. The compromise 1-pass scheme performs nearly as well as the full 2-pass algorithm, but with the same complexity as a fixed quantizer design. The adaptive schemes are shown to outperform the fixed quantizer used in earlier works, especially at high bit rates where the gain is up to 1.7 dB.