Fixed-length Codewords Research Articles

Fast and Efficient Entropy Coding Architectures for Massive Data Compression

The compression of data is fundamental to alleviating the costs of transmitting and storing massive datasets employed in myriad fields of our society. Most compression systems employ an entropy coder in their coding pipeline to remove the redundancy of coded symbols. The entropy-coding stage needs to be efficient, to yield high compression ratios, and fast, to process large amounts of data rapidly. Despite their widespread use, entropy coders are commonly assessed for some particular scenario or coding system. This work provides a general framework to assess and optimize different entropy coders. First, the paper describes three main families of entropy coders, namely those based on variable-to-variable length codes (V2VLC), arithmetic coding (AC), and tabled asymmetric numeral systems (tANS). Then, a low-complexity architecture for the most representative coder(s) of each family is presented—more precisely, a general version of V2VLC, the MQ, M, and a fixed-length version of AC and two different implementations of tANS. These coders are evaluated under different coding conditions in terms of compression efficiency and computational throughput. The results obtained suggest that V2VLC and tANS achieve the highest compression ratios for most coding rates and that the AC coder that uses fixed-length codewords attains the highest throughput. The experimental evaluation discloses the advantages and shortcomings of each entropy-coding scheme, providing insights that may help to select this stage in forthcoming compression systems.

Adaptive-Length Coding of Image Data for Low-Cost Approximate Storage

In the past few years, ever-increasing amounts of image data have been generated by users globally, and these images are routinely stored in cold storage systems in compressed formats. This article investigates the use of approximate storage that leverages the use of cheaper, lower reliability memories that can have higher error rates. Since traditional JPEG-based schemes based on variable-length coding are extremely sensitive to error, the direct use of approximate storage results in severe quality degradation. We propose an error-resilient adaptive-length coding (ALC) scheme that divides all symbols into two classes, based on their frequency of occurrence, where each class has a fixed-length codeword. This provides a balance between the reliability of fixed-length coding schemes, which have a high storage overhead, and the storage-efficiency of Huffman coding schemes, which show high levels of error on low-reliability storage platforms. Further, we use data partitioning to determine which bits are stored in approximate or reliable storage to lower the overall cost of storage. We show that ALC can be used with general non-volatile storage, and can substantially reduce the total cost compared to traditional JPEG-based storage.

Exploiting variable-length padding bits for decoder performance improvement with its application to compressed video transmission

In many practical communications systems, the number of bits transmitted by each frame is fixed, whereas the number of information bits to be transmitted can be variable. One example is a typical communication system that consists of a source encoder followed by a channel encoder, where the former generates a variable-length information sequence per source data and the latter converts a fixed-length information sequence into a fixed-length codeword. Therefore, dummy bits are often padded (or stuffed) to the information bits prior to channel encoding at the transmitter so as to fill the gap, and they are usually discarded after channel decoding at the receiver. This paper proposes a novel use of such padding bits (PBs) for improving the performance of channel codes. We first observe that by considering the PBs embedded in the information part of systematic block codes as known bits and expurgating them at the receiver, it is possible to enhance the performance of the channel decoders, provided that the PBs are judiciously rearranged in the information sequence and they are perfectly known at the receiver. Nevertheless, the length of the PBs is random by nature, and transmitting such side information per frame would reduce the throughput. Therefore, we also develop a novel detector that can estimate the PB length reliably without the help of explicit side information. Through computer simulations employing an actual turbo code, the effectiveness of the proposed receiver with the PB length detector is demonstrated in terms of frame error rate (FER) performance. Furthermore, as a practical example of the proposed technique, its application to typical video transmission systems is addressed, where the performance improvement in terms of peak signal-to-noise ratio (PSNR) is observed.

A Lightweight Contextual Arithmetic Coder for On-Board Remote Sensing Data Compression

The Consultative Committee for Space Data Systems (CCSDS) has issued several data compression standards devised to reduce the amount of data transmitted from satellites to ground stations. This paper introduces a contextual arithmetic encoder for on-board data compression. The proposed arithmetic encoder checks the causal adjacent neighbors, at most, to form the context and uses only bitwise operations to estimate the related probabilities. As a result, the encoder consumes few computational resources, making it suitable for on-board operation. Our coding approach is based on the prediction and mapping stages of CCSDS-123 lossless compression standard, an optional quantizer stage to yield lossless or near-lossless compression and our proposed arithmetic encoder. For both lossless and near-lossless compression, the achieved coding performance is superior to that of CCSDS-123, M-CALIC, and JPEG-LS. Taking into account only the entropy encoders, fixed-length codeword is slightly better than MQ and interleaved entropy coding.

Context-Adaptive Binary Arithmetic Coding With Fixed-Length Codewords

Context-adaptive binary arithmetic coding is a widespread technique in the field of image and video coding. Most state-of-the-art arithmetic coders produce a (long) codeword of a priori unknown length. Its generation requires a renormalization procedure to permit progressive processing. This paper introduces two arithmetic coders that produce multiple codewords of fixed length. Contrary to the traditional approach, the generation of fixed-length codewords does not require renormalization since the whole interval arithmetic is stored in the coder’s internal registers. The proposed coders employ a new context-adaptive mechanism based on variable-size sliding window that estimates with high precision the probability of the symbols coded. Their integration in coding systems is straightforward as demonstrated within the framework of JPEG2000. Experimental tests indicate that the proposed coders are computationally simpler than the MQ coder of JPEG2000 and the M coder of HEVC while achieving superior coding efficiency.

An efficient Variable-to-Fixed length encoding using multiplexed parse trees

We discuss an improved method of Variable-to-Fixed length code (VF code) encoding. A VF code is a coding scheme that splits an input text into a consecutive sequence of substrings, and then assigns a fixed length codeword to each substring. Since all the codewords have the same length, they are easily extracted, and thus, VF code is suitable for processing compressed texts directly. Almost Instantaneous VF code (AIVF code), which was proposed by Yamamoto and Yokoo in 2001, achieves a good compression ratio by using a set of parse trees. However, it requires more time and space for both encoding and decoding than does a classical VF code. In this paper, we prove that the set of parse trees of AIVF code can be multiplexed into a compact single tree and the original encoding and decoding procedures can be simulated using the compacted tree. We also give the upper and lower bounds of the number of nodes in the multiplexed parse tree, in addition to those of the number of nodes reduced from the original trees. The experimental results showed that the proposed method can encode natural language texts much faster than AIVF coding.

H-HIBASE: Compression Enhancement of HIBASE Technique Using Huffman Coding

HIBASE compression technique simply replaces the attribute values in a tuple with fixed length code-words. However, fixed length coding system is not an optimal compression technique because some redundancies occur in the compressed table. This redundancy can be avoided if we use Huffman code-words. Moreover, using Huffman code-word will ensure optimal compression as well as high performance operation. The objectives of the research are to i) develop a dictionary by applying the principle of Huffman coding, ii) compress the relational storage of HIBASE by applying dynamic Huffman coding, iii) develop algorithm to perform query operation on the compressed storage, iv) analyze the performance of the proposed system in terms of both storage and queries. The main contribution of this research is to develop a compression technique. It implies the enhancement of HIBASE technique using HUFFMAN coding (H-HIBASE) with better compression capability.

Video Watermarking Scheme Based on DWT and PCA for Copyright Protection

The distribution of digital products like audio and video are increasing rapidly over the networks, so the owners of such digital data are worried about their ownership protection. It may be possible that the third- party may claim the digital products as their own and misuse it in future. In order to overcome this problem, 'Video Watermarking Scheme Based on Principal Component Analysis and Wavelet Transform for Copyright Protection', is introduced for preventing illegal copying of their digital products. In this system, a Binary logo watermark is embedded in video frames for copyright protection. Principal Component Analysis (PCA) is applied to each block of the two bands (LL - HH) which results from Discrete Wavelet transform of the video frame. The watermark is embedded into the principal components of the LL blocks and HH blocks at different levels. Combining the DWT and PCA transform improves the performance of the watermark algorithm. This watermarking scheme shows no visible difference between the watermarked frames and the original frames i.e. imperceptible to the Human Visual System (HVS). It depicts the robustness against a wide range of attacks such as geometric transformation, histogram equalization, and gamma correction. Keywords -Advanced Encryption Standard (AES), Discrete wavelet transforms (DWT), Fixed-length codeword (FLC), Principle Component Analysis (PCA), Video Watermarking.

Rate-Distortion-Optimized Video Transmission Using Pyramid Vector Quantization

Conventional video compression relies on interframe prediction (motion estimation), intra frame prediction and variable-length entropy encoding to achieve high compression ratios but, as a consequence, produces an encoded bitstream that is inherently sensitive to channel errors. In order to ensure reliable delivery over lossy channels, it is necessary to invoke various additional error detection and correction methods. In contrast, techniques such as Pyramid Vector Quantisation have the ability to prevent error propagation through the use of fixed length codewords. This paper introduces an efficient rate distortion optimisation algorithm for intra-mode PVQ which offers similar compression performance to intra H.264/AVC and Motion JPEG 2000 while offering inherent error resilience. The performance of our enhanced codec is evaluated for HD content in the context of a realistic (IEEE 802.11n) wireless environment. We show that PVQ provides high tolerance to corrupted data compared to the state of the art while obviating the need for complex encoding tools.

Improving Parse Trees for Efficient Variable-to-Fixed Length Codes

We address the problem of improving variable-length-to-fixed-length codes (VF codes). A VF code that we deal here with is an encoding scheme that parses an input text into variable length substrings and then assigns a fixed length codeword to each parsed substring. VF codes have favourable properties for fast decoding and fast compressed pattern matching, but they are worse in compression ratio than the latest compression methods. The compression ratio of a VF code depends on the parse tree used as a dictionary. To gain a better compression ratio we present several improvement methods for constructing parse trees. All of them are heuristical solutions since it is intractable to construct the optimal parse tree. We compared our methods with the previous VF codes, and showed experimentally that their compression ratios reach to the level of state-of-the-art compression methods.

Improving Parse Trees for Efficient Variable-to-Fixed Length Codes

We address the problem of improving variable-length-to-fixed-length codes (VF codes). A VF code that we deal here with is an encoding scheme that parses an input text into variable length substrings and then assigns a fixed length codeword to each parsed substring. VF codes have favourable properties for fast decoding and fast compressed pattern matching, but they are worse in compression ratio than the latest compression methods. The compression ratio of a VF code depends on the parse tree used as a dictionary. To gain a better compression ratio we present several improvement methods for constructing parse trees. All of them are heuristical solutions since it is intractable to construct the optimal parse tree. We compared our methods with the previous VF codes, and showed experimentally that their compression ratios reach to the level of state-of-the-art compression methods.

On the Design of Perceptual MPEG-Video Encryption Algorithms

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this paper, some existing perceptual encryption algorithms of MPEG videos are reviewed and some problems, especially security defects of two recently proposed MPEG-video perceptual encryption schemes, are pointed out. Then, a simpler and more effective design is suggested, which selectively encrypts fixed-length codewords in MPEG-video bit streams under the control of three perceptibility factors. The proposed design is actually an encryption configuration that can work with any stream cipher or block cipher. Compared with the previously-proposed schemes, the new design provides more useful features, such as strict size-preservation, on-the-fly encryption and multiple perceptibility, which make it possible to support more applications with different requirements. In addition, four different measures are suggested to provide better security against known/chosen-plaintext attacks. </para>

Absolute value coding for robust and scalable video coding

Absolute value coding is introduced as a method for significantly reducing temporal drift within a motion compensated predictive video codec in the presence of loss. Drift reduction both improves error resilience and enables scalability by omission of parts of the bit-stream. In conjunction with matching pursuits, the system can be used to provide a displaced frame difference codec using fixed length codewords, which further improves error resilience and facilitates simple bit-stream editing.

Error-resilient first-order multiplexed source codes: performance bounds, design and decoding algorithms

This paper describes a new family of error-resilient variable-length source codes (VLCs). The codes introduced can be regarded as generalizations of the multiplexed codes described by Je/spl acute/gou and Guillemot. They allow to exploit first-order source statistics while, at the same time, being resilient to transmission errors. The design principle consists of creating a codebook of fixed-length codewords (FLCs) for high-priority information and in using the inherent codebook redundancy to describe low-priority information. The FLC codebook is partitioned into equivalence classes according to the conditional probabilities of the high-priority source. The error propagation phenomenon, which may result from the memory of the source coder, is controlled by choosing appropriate codebook partitions and index assignment strategies. In particular, a context-dependent index assignment strategy, called crossed-index assignment, is described. For the symbol error rate criterion, the approach turns out to maximize the cardinality of a set of codewords, called the code kernel, offering synchronization properties. The decoder resynchronization capability is shown to be further increased by periodic use of memoryless multiplexed codes. Theoretical and practical performances in terms of compression efficiency and error resilience are analyzed.

Image transmission over noisy channels with variable-coefficient fixed-length coding scheme

A variable-coefficient fixed-length coding scheme is proposed for wavelet-based image transmission over noisy channels. Multiple subband coefficients are grouped into an extended source symbol and coded as a fixed-length code word such that the extended source symbols have almost the same probabilities. Part of the codebook is fixed based on the observation of the coefficient spatial distribution patterns in each subband to alleviate the transmission of the codebook. The remaining code positions within the fixed-length codebook can be utilized to combat channel errors by carefully arranging the code positions or be filled with other frequently appearing coefficient sequences to achieve higher compression ratio.

A high-quality fixed-length compression scheme for color images

We present a new compression method which compresses 8/spl times/8 picture blocks by fixed-length codewords. The compression operation is performed on the discrete cosine transforms, DCT, of each block. As a result, our method combines the distinct advantage of being fixed-length with the high image quality obtained by the DCT based compression methods. Our method has excellent error-resistance characteristics since it does not have the synchronization and error propagation problems inherent in variable-length coding methods.

Arithmetic coding into fixed-length codewords

Arithmetic coding is known to be optimal in compressing strings of independent symbols, the probabilities of which are given. However the method has some disadvantages that the present variant tries to overcome. The idea here is to apply arithmetic coding piecewise, by cutting the process regularly. The result consists of fixed-length sequences of bits, representing variable-length substrings of the source. For implementation reasons, the bit sequences are composed of machine words, allowing one to use basic arithmetic efficiently. The compression gain approaches the optimum when the sequence size is increased.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Adaptive channel error protection of subband encoded images

Protection of images that are encoded using subband coding from channel error is addressed. In this scheme the low-pass subband is encoded using DPCM (differential pulse-code modulation), and the other subbands are encoded using a scalar quantizer. The quantizers are all Lloyd-Max quantizers, from which the representation levels have fixed length codewords. First, considering only single errors in each codeword, a channel error distortion measure is derived for each quantizer, that is, for each subband. Codewords are assigned to the quantizer representation levels, yielding a low value of the distortion measure. Next, sets S/sub ij/ consisting of the jth bit from subband i are formed. Each set S/sub ij/ is assigned a particular BCH code C/sub ij/. An algorithm that optimally assigns BCH codes C/sub ij/ to each set S/sub ij/, based on a channel error distortion measure for the entire image, is derived. The protection scheme is adaptive, because each set of bits within each subband can be assigned a different error protection code. Examples show that this approach is preferable to assigning equal error protection codes to each set of bits. It is shown that in the case of a channel error probability of 10/sup -3/, only 5% to 10% extra bits are needed for adequate channel error protection.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Digital line segment coding: A new efficient contour coding scheme

A new coding scheme is proposed for two-tone image contours. The basic idea is to detect digital line segments on the contour and code them using fixed- or variable-length codewords; the present work deals mainly with fixed-length codewords. It is demonstrated that the conventional contour run length coding by Freeman&apos;s chain code is a special case of this scheme. The data compressibility of the scheme is studied and the test results on several contours are presented. The results show that the present scheme is superior to the conventional scheme.

Adaptive Companding of Picture Signals in a Predictive Coder

This paper describes a technique for varying the quantization characteristics in a Differential Pulse Code Modulation (DPCM) System. A multiplier, based on already transmitted picture elements (pels) which are spatially close to the pel being coded, is used to multiply the prediction error in a DPCM system. This multiplied prediction error is quantized by a fixed quantizer. Coarseness of quantization is thus dependent on the value of the multiplier, which is adjusted on the basis of the sensitivity of the human observers to quantization errors. The implementation is particularly useful in those cases where the quantizer outputs are coded using fixed length code words. Computer simulations on a variety of pictures indicate that a good quality picture can be produced by using a quantizer having between 8 to 10 levels and a two-dimensional predictor. Similar picture quality can be obtained by a simple nonadaptive previous element DPCM system having a quantizer with 13 to 16 levels.