Context-based Arithmetic Encoding Research Articles

High Efficiency EBCOT with Parallel Coding Architecture for JPEG2000

This work presents a parallel context-modeling coding architecture and a matching arithmetic coder (MQ-coder) for the embedded block coding (EBCOT) unit of the JPEG2000 encoder. Tier-1 of the EBCOT consumes most of the computation time in a JPEG2000 encoding system. The proposed parallel architecture can increase the throughput rate of the context modeling. To match the high throughput rate of the parallel context-modeling architecture, an efficient pipelined architecture for context-based adaptive arithmetic encoder is proposed. This encoder of JPEG2000 can work at 180 MHz to encode one symbol each cycle. Compared with the previous context-modeling architectures, our parallel architectures can improve the throughput rate up to 25%.

Binary shape coding using finite automata

Two new binary shape-coding techniques that are based on finite automata methods are proposed. Both contour-based and bitmap-based approaches to shape coding are investigated using one-dimensional weighted finite automata (1D-WFA) and generalised finite automata (GFA) algorithms, respectively. We evaluate the fidelity of shape representation, using 1D-WFA and GFA methods in intraframe mode and compare the performance of the proposed coding techniques against each other and with the benchmark, context-based arithmetic encoding (CAE) of shapes used in MPEG-4. It is found that the GFA method is more suitable for video applications than 1D-WFA and therefore it is adapted to operate in interframe mode. More importantly, GFA is the first shape-coding technique reported to date that has the unique advantage of shape processing in the compressed domain. This is due to the fact that the shape representation in the compressed domain using GFA facilitates processing at the expense of less compression efficiency compared with MPEG-4 CAE. Moreover, shapes encoded using the GFA method can be decoded at any desirable resolution.

A multisymbol context-based arithmetic coding architecture for MPEG-4 shape coding

MPEG-4 shape coding comprises context-based arithmetic encoding (CAE) as its centerpiece. Since the CAE algorithm has a complicated coding procedure and strong data dependency, it is hard to exploit its pipeline and parallel facilities. Furthermore, to encode multiple symbols within one clock cycle, it needs to overcome the issues of extracting multiple contexts of these symbols, deriving multiple probabilities from these contexts, and performing multiple multiplicative range update operations. This paper presents an efficient pipelined multisymbol CAE architecture for real-time MPEG-4 shape encoding. The proposed design is based on the inherent characteristics of binary alpha blocks as well as the numerical properties of the probabilities indexed by the contexts, and it is capable of encoding either a singe symbol or multiple symbols within each clock cycle. To overcome the aforementioned issues under the consideration of the hardware cost and the critical path delay, only symbols with a particular set of contexts are chosen to be processed simultaneously within the same clock cycle. Theoretical analysis shows that the majority of symbols have contexts belonging to this particular set, and therefore CAE processing can be significantly accelerated. An example VLSI implementation of proposed architecture that encodes two symbols within each clock cycle without sacrificing the clock rate can achieve a speedup of 1.47 in comparison with traditional CAE architectures. This particular two-symbol design can support MPEG-4 Main Profile at levels 3 and 4 under extreme and typical conditions, respectively. When synthesized from Verilog RTL design by using TSMC 0.35-/spl mu/m 1P4M CMOS technology, the design can run at 90 MHz.

Progressive encoding of complex isosurfaces

We present a progressive encoding technique specifically designed for complex isosurfaces. It achieves better rate distortion performance than all standard mesh coders, and even improves on all previous single rate isosurface coders. Our novel algorithm handles isosurfaces with or without sharp features, and deals gracefully with high topologic and geometric complexity. The inside/outside function of the volume data is progressively transmitted through the use of an adaptive octree, while a local frame based encoding is used for the fine level placement of surface samples. Local patterns in topology and local smoothness in geometry are exploited by context-based arithmetic encoding, allowing us to achieve an average of 6.10 bits per vertex (b/v) at very low distortion. Of this rate only 0.65 b/v are dedicated to connectivity data: this improves by 24% over the best previous single rate isosurface encoder.

Transform domain LMS-based adaptive prediction for lossless image coding

This paper is concerned with adaptive prediction for lossless image coding. A new predictor is proposed. This predictor involves two major steps: constructing a good predictor for each pixel using the transform domain LMS algorithm and adaptively combining it with a set of fixed predictors. The first step is targeting areas where simple predictors do not perform well, while the second step is an effective method to reduce the modelling costs associated with the uncertainty of the models. When a context-based arithmetic encoder is used to encode the prediction error, the compression performance of the proposed algorithm is better than or comparable to that of other published algorithms.

Optimal buffered compression and coding mode selection for MPEG-4 shape coding

We propose an optimal buffered compression algorithm for shape coding as defined in the forthcoming MPEG-4 international standard. The MPEG-4 shape coding scheme consists of two steps: first, distortion is introduced by down and up scaling; then, context-based arithmetic encoding is applied. Since arithmetic coding is "lossless," the down up scaling step is considered as a virtual quantizer. We first formulate the buffer-constrained adaptive quantization problem for shape coding, and then propose an algorithm for the optimal solution under buffer constraints. Previously, the fact that a conversion ratio (CR) of 1/4 makes a coded image irritating to human observers for QCIF size was reported for MPEG-4 shape coding. Therefore, careful consideration for small size images such as QCIF should be given to prevent coded images from being unacceptable. To this end, a low bit rate tuned algorithm is proposed in this paper as well. Experimental results are given using an MPEG-4 shape codec.

Adaptive context-based arithmetic coding of arbitrary contour maps

An efficient technique for encoding arbitrary contours is presented. It is based on the concept of transition points of a contour map and relies on a new four-symbol adaptive context-based arithmetic encoder (CAE) that calculates contexts in the (binary) domain of the contour map. The results obtained with this new technique, applied to the compression of image partitions, are substantially better than those previously attained, showing a clear superiority over adaptive CAE-based differential chain coding and also over the MPEG-4 shape coding.

Shape compression of moving objects using context-based arithmetic encoding

This paper deals with an approach to the compression of 2-D shape information. Specifically, the approach utilises a block-based context-based arithmetic encoding method to exploit both spatial and temporal redundancy in sequences of shapes. The method is shown to be highly efficient in comparative tests. In addition, it is demonstrated that context-based arithmetic encoding is easily extended for the coding of interlaced shape sources and for encoding any source in a scalable and/or error resilient manner. The application of the technique is in the compression of video object shapes within the framework of object-based video coding. The proposed algorithm is part of the MPEG-4 video specification.

Scan interleaving based scalable binary shape coding

Abstract In this paper, we propose scan interleaving based shape coding (SISC) as a spatial scalable coding algorithm for binary shape. A typical scalable video system has two or more scalable layers. These are the base layer and the associated enhancement layers. In the proposed spatial scalable binary shape coding algorithm, scan interleaving based data encoding (SI) scheme is proposed for the enhancement layer coding. And context-based arithmetic encoding (CAE) method is employed for entropy coding of binary shape data in each scalable layer. SI scheme efficiently exploits the spatial redundancy of the scalable layers. For reducing the temporal redundancy, inter-frame coding based on motion compensation is employed. The major advantages of SISC are high coding gain, low complexity, and consistency with MPEG-4 non-scalable binary shape coding. High coding gain is achieved from the method of coded-scan-line data analysis, which uses exclusive-OR operation on top and bottom reference pixels. Furthermore, by referring the lower layer motion vectors for its inter-frame coding process, SISC also saves some computational overhead of enhancement layer coding. The proposed technique is, currently, adopted in the Working Draft of MPEG-4 Version 2. SISC supports both the frame-based coding mode and the block-based coding mode. The block-based SISC, as in MPEG-4, is mainly described in this paper.

A new vertex-based binary shape coder for high coding efficiency

This paper proposes a new vertex-based binary shape intra coding scheme that generates a set of vertices reducing shape reconstruction error and efficiently encodes the vertices. The conventional vertex-based coding scheme uses the iterated refinement method (IRM) for vertex selection and the object-adaptive vertex encoding (OAVE) for vertex transmission. In the proposed scheme, we introduce a vertex adjustment method to be applied to the vertices selected by the IRM. The vertex adjustment method significantly reduces the reconstruction error of binary shapes. For efficient transmission of vertices, we also propose 1D vertex detection, vertex reordering and initial vertex encoding methods. Furthermore, a conditional differential chain coding is presented for efficient lossless coding of contours. Experimental results show that the proposed vertex-based intra coding scheme reduces coded bits by 17–29% compared with the conventional vertex-based coding scheme, and by up to 27% compared with the intra coding mode of the context-based arithmetic encoding (CAE) scheme of the MPEG-4 Video Verification Model.

Binary shape coding using baseline-based method

Here, we propose a new shape-coding algorithm called baseline-based binary shape coding (BBSC), where the outer or inner contours of an arbitrarily shaped object are represented by traced one-dimensional (l-D) data from the baseline with turning points (TP's). There are two coding modes, i.e., the intra and inter modes as in texture coding. In the intra mode, the differential values of the neighboring 1-D distance values and TP's corresponding to the given shape are encoded by the entropy coder. In the inter mode, object identification, global shape matching and local contour matching are employed for motion compensation/estimation. Lossy shape coding is enabled by variable sampling in each contour segment or by allowing some predefined error when performing motion compensation. We compare the proposed method with the bitmap-based method of context-based arithmetic encoding (CAE). Simulation results show that the proposed method is better than CAE in coding efficiency for intra mode and better in subjective quality for both intra and inter modes, although the CAE method has performed better than the proposed method in inter mode.

MPEG-4 standardized methods for the compression of arbitrarily shaped video objects

MPEG-4 is the most recent standard for audio-visual representation to be published by the International Organization for Standardization. One of the many new features of MPEG-4 is its ability to represent two-dimensional video objects of arbitrary shape. For this purpose, MPEG-4 uses the conventional motion-compensated discrete cosine transform syntax for color/texture coding and augments this with an explicit compressed representation of the video object's shape. This paper is intended as a tutorial in the means of encoding and decoding arbitrarily shaped video objects as specified by MPEG-4. The major emphasis of the paper is on explaining the compression technology associated with the normative shape representation, i.e., block-based context-based arithmetic encoding, but some new aspects associated with arbitrarily shaped texture coding are also highlighted. The MPEG-4 specifications are presented in an informal way, and the motivations underlying the algorithm are clarified. In addition, effective methods are suggested for performing many of the nonnormative encoding tasks, and several encoding performance tradeoffs are illustrated.