Low-complexity Encoding Research Articles

Unidirectional Distributed Video Coding for Low Cost Video Encoding

Distributed video coding (DVC) is an emerging video coding approach in the new era, particularly attractive due to its flexibility to introduce very simple encoder structures. This feature could be very effectively utilized in the design of low cost video cameras. However, the DVC architecture commonly discussed in research literature has a fundamental drawback of involving a feedback channel between the encoder and the decoder, which restrains itself from being used in video storage based applications. In this paper, we discuss a solution to the above problem in DVC, with a novel unidirectional architecture. In the proposed design, the feedback channel is suppressed and the encoded (compressed) bit stream can be transferred onto storage media for offline processing. The proposed decoder uses the spatial and temporal properties of the video sequence to refine the side information for iterative decoding, with the repeated use of same parity bit stream. The simulation results depict a significantly improved performance over other conventional video coding techniques proposed for use in low to middle end video equipments, while involving a very low encoder complexity.

Semi-random LDPC codes for CDMA communication over non-linear band-limited satellite channels

This paper considers the application of low-density parity check (LDPC) error correcting codes to code division multiple access (CDMA) systems over satellite links. The adapted LDPC codes are selected from a special class of semi-random (SR) constructions characterized by low encoder complexity, and their performance is optimized by removing short cycles from the code bipartite graphs. Relative performance comparisons with turbo product codes (TPC) for rate 1/2 and short-to-moderate block sizes show some advantage for SR-LDPC, both in terms of bit error rate and complexity requirements. CDMA systems using these SR-LDPC codes and operating over non-linear, band-limited satellite links are analysed and their performance is investigated for a number of signal models and codes parameters. The numerical results show that SR-LDPC codes can offer good capacity improvements in terms of supportable number of users at a given bit error performance.

The Q-matrix Low-Density Parity-Check codes

This paper presents a matrix permuting approach to the construction of Low-Density Parity-Check (LDPC) code. It investigates the structure of the sparse parity-check matrix defined by Gallager. It is discovered that the problem of constructing the sparse parity-check matrix requires an algorithm that is efficient in search environments and also is able to work with constraint satisfaction problem. The definition of Q-matrix is given, and it is found that the queen algorithm enables to search the Q-matrix. With properly permuting Q-matrix as sub-matrix, the sparse parity-check matrix which satisfied constraint condition is created, and the good regular-LDPC code that is called the Q-matrix LDPC code is generated. The result of this paper is significant not only for designing low complexity encoder, improving performance and reducing complexity of iterative decoding arithmetic, but also for building practical system of encodable and decodable LDPC code.

Low Encoding Complexity Video Compression Based on Low-Density Parity Check Codes

Conventional video compression methods generally require a large amount of computation in the encoding process because they perform motion estimations. In order to reduce the encoding complexity for video compression, this paper proposes a new video compression method based on low-density parity check codes. The proposed method is suitable for resource-constrained devices such as mobile phones and satellite cameras.

LSP quantization by a union of locally trained codebooks

We present a fixed rate encoding scheme for the line spectrum pair (LSP) representation of an LPC-filter, based on Gaussian mixture (GM) modeling. For each mixture component, we construct a codebook by a union of product quantizers. Each local codebook is trained, independently, using a clustering scheme similar to the generalized Lloyd algorithm (GLA), over synthetic data. The training algorithm iterates fast, due to low complexity encoding, and converges in few iterations. The overall codebook is a combination of local codebooks, and inherits their high performance, while having a moderate complexity. We provide numerical results for average spectral distortion (SD) of the proposed encoder, and benchmark them by a lower bound, according to high-rate theory. We achieve an average SD (full-band measure) of 1 dB at 23 b/frame, for speech signals sampled at 8 kHz and LPC of order 10. By tolerating additional complexity, we reach a SD within 0.01 dB of the lower bound.

Block Codes for the Hard-Square Model

The hard-square model is a two-dimensional (2-D) constrained system consisting of all binary arrays on a rectangular grid in which 1's are isolated both horizontally and vertically. This paper proposes algorithms to search for single-state and finite-state block codes with rectangular codewords that satisfy the hard-square constraint. Although the codeword size is small, single-state block codes with coding rates larger than 0.5 can be designed. Letting the 2-D constrained sequences have finite memory increases the achievable coding rate. A method for designing low-complexity encoders and decoders is also presented. When the codeword size increases, the coding rate asymptotically approaches the capacity but with rapidly increasing complexity of the encoder and decoder.

Low-Complexity MPEG-4 Shape Encoding towards Realtime Object-Based Applications

Although frame-based MPEG-4 video services have been successfully deployed since 2000, MPEG-4 video coding is now facing great competition in becoming a dominant player in the market. Object-based coding is one of the key functionalities of MPEG-4 video coding. Realtime object-based video encoding is also important for multimedia broadcasting for the near future. Object-based video services using MPEG-4 have not yet made a successful debut due to several reasons. One of the critical problems is the coding complexity of object-based video coding over frame-based video coding. Since a video object is described with an arbitrary shape, the bitstream contains not only motion and texture data but also shape data. This has introduced additional complexity to the decoder side as well as to the encoder side. In this paper, we have analyzed the current MPEG-4 video encoding tools and proposed efficient coding technologies that reduce the complexity of the encoder. Using the proposed coding schemes, we have obtained a 56 percent reduction in shape-coding complexity over the MPEG-4 video reference software (Microsoft version, 2000 edition).

Joint<tex>$(3, k)$</tex>-Regular LDPC Code and Decoder/Encoder Design

Recently, low-density parity-check (LDPC) codes have attracted a lot of attention in the coding theory community. However, their real-world applications are still problematic mainly due to the lack of effective decoder/encoder hardware design approaches. In this paper, we present a joint (3,k)-regular LDPC code and decoder/encoder design technique to construct a class of (3,k)-regular LDPC codes that not only have very good error-correcting capability but also exactly fit to high-speed partly parallel decoder and low-complexity encoder implementations. We also develop two techniques to further modify this joint design scheme to achieve more flexible tradeoffs between decoder hardware complexity and decoding speed.

Design of Efficiently Encodable Moderate-Length High-Rate Irregular LDPC Codes

This paper presents a new class of irregular low-density parity-check (LDPC) codes of moderate length (10/sup 3//spl les/n/spl les/10/sup 4/) and high rate (R/spl ges/3/4). Codes in this class admit low-complexity encoding and have lower error-rate floors than other irregular LDPC code-design approaches. It is also shown that this class of LDPC codes is equivalent to a class of systematic serial turbo codes and is an extension of irregular repeat-accumulate codes. A code design algorithm based on the combination of density evolution and differential evolution optimization with a modified cost function is presented. Moderate-length, high-rate codes with no error-rate floors down to a bit-error rate of 10/sup -9/ are presented. Although our focus is on moderate-length, high-rate codes, the proposed coding scheme is applicable to irregular LDPC codes with other lengths and rates.

Efficient real-time frame layer rate control technique for low bit rate video over WLAN

A real-time frame-layer rate control algorithm is proposed for low bit rate video coding over IEEE 802.11 wireless local area network (WLAN). The proposed rate control method performs bit allocation at the frame level to minimize the average distortion over an entire sequence as well as variations in distortion between frames. A new frame-layer rate-distortion model is derived, and a non-iterative optimization method is used for low computational complexity. The proposed algorithm produces low encoding time delay, and is suitable for real-time low-complexity video encoder. Experimental results indicate that the proposed control method provides better visual and PSNR performance than the existing TMN8 rate control method.

Loose composite constraint codes and their application in DVD

Constrained coding is used in recording systems to translate an arbitrary sequence of input data to a channel sequence with special properties required by the physics of the medium. Very often, more than one constraint is imposed on a recorded sequence; typically, a run-length constraint is combined with a spectral-null constraint. We introduce a low-complexity encoder structure for composite constraints, based on loose multimode codes. The first channel constraint is imposed strictly, and the second constraint is imposed in a probabilistic fashion. Relaxing the second constraint is beneficial because it enables higher code rates and simplifies the encoder. To control the second constraint a multimode encoder is used. We represent a set of multimode coded sequences by a weighted trellis and propose using a limited trellis search to select optimal output. Using this method, we modify the EFM+ code used in digital versatile disk (DVD). We combine EFM+'s run-length constraint with the first- and second-order spectral-null constraints. The resulting EFM++ code gives more than 10-dB improvement in suppression of low-frequency spectral content in the servo bandwidth over the original EFM+ code with the same complexity.

A Lagrangian optimization approach to complexity-constrained TSVQ

We present a new variable rate tree-structured vector quantizer (TSVQ) design algorithm, in which the complexity-distortion tradeoff is explicitly managed using a Lagrangian optimization approach. The algorithm is greedy and uses subvector distortion measures to lower the encoding complexity. We show that we can obtain low complexity encoders for the Gauss-Markov source with similar distortion to that observed on standard variable rate TSVQ.

Combi-codes for DC-free runlength-limited coding

We present a new coding scheme for DC-free runlength-limited (RLL) codes. This scheme is based on the combination of two codes, a main code and a substitution code, both operating on symbols of a fixed length n. The substitution code has a special structure, i.e., for each n-bit symbol, there are two possible channel words, which have opposite parity and the same next-state in the underlying finite-state machine (FSM). The advantages of this systematic structure of the code are: guaranteed DC-control, ECC-symbol oriented coding, and low-complexity look-ahead DC-control encoding. A design for an efficient combi-code for both for EFM-like RLL constraints (d=2, k=10) and for (d=1, k=7) RLL constraints, is outlined.

A systematic approach to the construction of bandwidth-efficient multidimensional trellis codes

We present a unified approach to the construction of multidimensional trellis codes that have small constellation expansion ratio (CER) and small peak-to-average power ratio (PAR) and hence are of high bandwidth efficiency. In the approach, we extend Wei's (1987) construction to dimensionalities other than a power of two and propose a low-complexity encoder. We also present a general partition technique that gives geometrically uniform partitions with a good distance profile. The proposed method can generate many good codes including previously reported Ungerboeck codes, Gallager-Calderbank-Sloane codes, and Wei codes with quadrature amplitude modulation signals. Some newly discovered six-dimensional trellis codes are compared with these known codes on their CER, PAR, effective coding gain, and encoder/decoder complexities.

Design, performance, and complexity analysis of residual trellis-coded vector quantizers

Multistage trellis-coded vector quantization (MS-TCVQ) is developed as a constrained trellis source-coding technique. The performance of the two-stage TCVQ is studied for Gaussian sources. Issues of stage-by-stage design, output alphabet selection, and complexity are addressed with emphasis on selecting and partitioning the stage codebooks. For a given rate, MS-TCVQ achieves low encoding and storage complexity compared to TCVQ, and comparisons with same-dimensional multistage vector quantization indicate a 0.5-3-dB improvement in signal-to-quantization-noise ratio.

Video coding using motion compensation with polynomial motion vector fields

Abstract This paper describes a method for motion-compensated compression of video sequences. The proposed method enables very efficient encoding of video frames partitioned into arbitrary-shaped regions. The implementation described in this paper employs simple quadtree-based segmentation of video frames and a polynomial model of the motion vector field. Polynomial motion vector fields are estimated using an iterative minimization method. Application of complex polynomial motion vector fields to coding of video requires their compact encoding, especially for low bit-rate applications. The paper proposes novel algorithms enabling low-complexity encoding of polynomial motion vector fields which are optimal in least mean square error sense. Specifically, an efficient method for merging of regions resulting from quadtree segmentation is presented. The advantage of this method is its ability to achieve large reduction in the number of regions in typical coded sequences with only a minor increase of prediction error. An algorithm for reduction of the number of polynomial motion vector field coefficients is also presented. This algorithm enables adaptation of the motion vector field model to the complexity of motion in the coded scene. The problem of quantization of polynomial motion coefficients is also addressed. Performance of the proposed algorithms has been evaluated in a simple motion-compensated DCT codec and compared to an ITU-T H.263 codec. Simulations show that a consistent reduction of bit-rate in excess of 25% can be achieved over a wide range of sequences. Depending on the envisaged application the described algorithms can be used together with segmentation of desired accuracy and therefore provide simultaneously high coding efficiency as well as ability of content-based encoding of video.

Enhanced multistage vector quantization for SAR raw data compression

MultiStage Vector Quantization(MSVQ) can achieve very low encoding and storage complexity in comparison to unstructured vector quantization. However, the conventional MSVQ is suboptimal with respect to the overall performance measure. This paper proposes a new technology to design the decoder codebook, which is different from the encoder codebook to optimise the overall performance. The performance improvement is achieved with no effect on encoding complexity, both storage and time consuming, but a modest increase in storage complexity of decoder.

Optimum bit rate pyramid coding with low computational and memory requirements

This paper presents the optimum bit allocation for fixed rate pyramid coding structures which use a lowpass filter with nominal bandwidth of /spl pi//4 for predecimation filtering. This technique results in about 32% less in the computational complexity and 20% less in the memory requirements than the conventional filters used for pyramid coding. Three different algorithms are introduced. In the first algorithm the decimated image is transmitted at 8 bpp and the difference image is DCT-encoded. In the second algorithm the decimated image is encoded using BTC and the difference image is DCT-encoded, while in the third algorithm the decimated image is BTC-encoded with further quantization of the DCT coefficients of the difference image. These algorithms achieve high compression rate and allow at the same time a low complexity encoder. >

Maximum-likelihood trellis decoding technique for balanced codes

A low-complexity encoding and maximum-likelihood trellis decoding (MLTD) technique for nonlinear balanced codes is presented. The technique is illustrated by the design of a (16, 9, 4) balanced code.

Low-complexity subband encoding for HDTV images

The transmission of high-definition television (HDTV) signals on available digital networks and satellites requires the adoption of sophisticated compression techniques to limit the bit rate requirements and to provide high-quality and reliable service to customers. For processing and transmission of image signals, a low-complexity codec without visible degradation is desired. A low-complexity intraframe subband image coding algorithm is developed. The low band is DPCM encoded and the high bands are PCM encoded. An efficient entropy coder is designed which reduces the overall bit rate significantly. It is shown that high-quality HDTV images can be obtained at as low a bit rate as 45 Mb/s or less with a very low-complexity encoder. For dividing the image into subbands, a new class of quadrature mirror filters (QMFs) called generalized quadrature mirror filters (GQMFs) is used for filtering. Performance is also evaluated by using short kernel filters (SKFs), which are easy to implement and require very few computations. >