Run-length Coding Research Articles

A unified approach to reduce soc test data volume, scan power and testing time

We present a test resource partitioning (TRP) technique that simultaneously reduces test data volume, test application time, and scan power. The proposed approach is based on the use of alternating run-length codes for test data compression. We present a formal analysis of the amount of data compression obtained using alternating run-length codes. We show that a careful mapping of the don't-cares in precomputed test sets to 1's and 0's leads to significant savings in peak and average power, without requiring either a slower scan clock or blocking logic in the scan cells. We present a rigorous analysis to show that the proposed TRP technique reduces testing time compared to a conventional scan-based scheme. We also improve upon prior work on run-length coding by showing that test sets that minimize switching activity during scan shifting can be more efficiently compressed using alternating run-length codes. Experimental results for the larger ISCAS89 benchmarks and an IBM production circuit show that reduced test data volume, test application time, and low power-scan testing can indeed be achieved in all cases.

Run-length coding extensions for high performance hardware data compression

The optimal placement of a run-length coding extension to a dictionary-based lossless data compression algorithm is investigated. A hardware implementation of the proposed extension is completed and integrated into an existing design. The new hardware is benchmarked against commercially available software and hardware compression methods. Run-length coding replaces repetitive, identical sequences of a symbol with a pair formed by a code indicating the repeating symbol plus a code indicating the length or number of repetitions that occurred. This method of coding is of limited use for general compression due to its relatively poor performance. However, good results can be achieved when used as an extension to a general lossless data compression algorithm where it can improve compression, targeting the coding of repetitive data formats such as zeroes in memory or fax pages or a uniform colour in image backgrounds. It is shown that the run-length coding method can be extended to support more complex repeating patterns with little extra cost in terms of hardware or speed but providing significant superior compression performance.

A method for compressing test data based on Burrows-Wheeler transformation

The overall throughput of automatic test equipment (ATE) is affected by the download time of test data. An effective approach to the reduction of the download time is to compress test data before the download. A compression algorithm for test data should meet two requirements: lossless and simple decompression. In this paper, we propose a new test data compression method that aims to fully utilize the unique characteristics of test data compression. The key idea of the proposed method is to perform the Burrows-Wheeler transformation on the sequence of test patterns and then to apply run-length coding. Experimental results show that our compression method performs better than six other methods for compressing test data. The average compression ratio of the proposed method performed on 15 test data sets is 94.6, while that for the next best one, Gzip, is 65.0. The experimental results also show that our method indeed reduces the download time significantly, provided a dedicated hardware decompressor is employed.

2D-pattern matching image and video compression: theory, algorithms, and experiments

In this paper, we propose a lossy data compression framework based on an approximate two-dimensional (2D) pattern matching (2D-PMC) extension of the Lempel-Ziv (1977, 1978) lossless scheme. This framework forms the basis upon which higher level schemes relying on differential coding, frequency domain techniques, prediction, and other methods can be built. We apply our pattern matching framework to image and video compression and report on theoretical and experimental results. Theoretically, we show that the fixed database model used for video compression leads to suboptimal but computationally efficient performance. The compression ratio of this model is shown to tend to the generalized entropy. For image compression, we use a growing database model for which we provide an approximate analysis. The implementation of 2D-PMC is a challenging problem from the algorithmic point of view. We use a range of techniques and data structures such as k-d trees, generalized run length coding, adaptive arithmetic coding, and variable and adaptive maximum distortion level to achieve good compression ratios at high compression speeds. We demonstrate bit rates in the range of 0.25-0.5 bpp for high-quality images and data rates in the range of 0.15-0.5 Mbps for a baseline video compression scheme that does not use any prediction or interpolation. We also demonstrate that this asymmetric compression scheme is capable of extremely fast decompression making it particularly suitable for networked multimedia applications.

Threshold-adjusted EZW Codec의 설계와 구현

본 논문은 웨이브릿 계수를 활용하여 영상 압축을 수행하는 EZW(Embedded Zerotree Wavelet) 부호화의 성능 개선에 대한 방법을 제시한다. EZW부호화는 웨이브릿 계수를 그 중요도에 따라 POS, NEG, IZ, ZTR의 4개의 심벌을 사용하여 부호화를 수행한다. 본 연구에서는 EZW 부호화에 웨이블릿 계수 threshold 방법을 적용하여 성능을 개선하였다. 시스템 전체적으로는 계수 threshold 방법을 적용하여 전체 부호화 시간을 단축하였으며, run-length 부호화와 산술 부호화를 적용하여 영상을 최대한으로 압축하였다. 마지막으로 실험을 통하여 EZW 부호화 방법에 적용된 계수 조정 값을 조절하여, 값의 변화에 따른 입력 영상과 복원 영상을 비교 분석한 결과를 제시하였다. In this paper, we propose a method for the improvement of EZW encoding algorithm. The EZW algorithm encodes wavelet coefficients using 4 symbols such as POS(POsitive), NEG(NEGative), IZ(Isolated Zero), and ZTR(ZeroTreeRoot) which are determined by the significance of wavelet coefficients. In this paper, we applied threshold to wavelet coefficients to improve the EZW algorithm. The coefficients below the threshold are adjusted to zero to generate more ZTR symbols in the encoding process. The overall EZW image compression system is constructed using run-length coding and arithmetic coding. The system shows remarkable results for various images. We finally present experimentation results.

Context conditioning and run-length coding for hybrid, embedded progressive image coding

An analysis of spatial context conditioning and run-length coding in embedded progressive, wavelet-based image coding is presented. The analysis shows that run-length coding of certain context subsequences is superior to pure entropy coding, both in terms of coding performance and of execution speed. Based on these considerations, a novel, intuitive context conditioning scheme using a spatial distance model to describe the statistics of significant coefficients is proposed. The results for the proposed coding scheme are competitive to the best coding schemes found in the literature.

Fast variable run-length coding for embedded progressive wavelet-based image compression

Run-length coding has attracted much attention in wavelet-based image compression because of its simplicity and potentially low complexity. The main drawback is the inferior RD-performance compared to the state-of-the-art-coder SPIHT. In this paper, we concentrate on the embedded progressive run-length code of Tian and Wells (1996, 1998). We consider significance sequences drawn from the scan in the dominant pass. It turns out that self-similar curves for scanning the dominant pass increase the compression efficiency significantly. This is a consequence of the correlation of direct neighbors in the wavelet domain. This dependence can be better exploited by using groups of coefficients, similar to the SPIHT algorithm. This results in a new and very fast coding algorithm, which shows performance similar to the state-of-the-art coder SPIHT, but with lower complexity and small and fixed memory overhead.

Rate 8/9 sliding block distance-enhancing code with stationary detector

A new distance-enhancing code for partial-response magnetic recording channels eliminates most frequent errors, while keeping the two-step code trellis time invariant. Recently, published trellis codes either have lower code rates or result in time-varying trellises with a period of nine, thus requiring a higher complexity of detectors and code synchronization. The new code introduces dependency between code words in order to achieve the same coding constraints as the 8/9 time-varying maximum transition runlength (TMTR) code, with the same code rate, but resulting in a trellis that has a period of 2. This code has been applied to the E/sup 2/PR4 and a 32-state generalized partial response (GPR) ISI target. The resulting two-step trellises have 14 and 28 states, respectively. Coding gain is demonstrated for both targets in additive white Gaussian noise.

System-on-a-chip test-data compression and decompression architectures based on Golomb codes

We present a new test-data compression method and decompression architecture based on variable-to-variable-length Golomb codes. The proposed method is especially suitable for encoding precomputed test sets for embedded cores in a system-on-a-chip (SoC). The major advantages of Golomb coding of test data include very high compression, analytically predictable compression results, and a low-cost and scalable on-chip decoder. In addition, the novel interleaving decompression architecture allows multiple cores in an SoC to be tested concurrently using a single automatic test equipment input-output channel. We demonstrate the effectiveness of the proposed approach by applying it to the International Symposium on Circuits and Systems' benchmark circuits and to two industrial production circuits. We also use analytical and experimental means to highlight the superiority of Golomb codes over run-length codes.

A new DC- and Nyquist-free trellis code for partial response class-I and class-II channels

A 16/20 (0, 6) dc- and Nyquist-free trellis code for the partial response class-I (PR1) and class-II (PR2) channels has been developed. With a Lorentzian pulse, this code showed a coding gain of 1.2 dB for the PR1 channel and 2.2 db for the PR2 channel at a user bit density of 3.0, compared with the conventional 16/17 (0, 6/6) run-length limited code for the extended partial response class-IV (EPR-I) channel in error-rate simulation. With a pulse with dc response, this code showed a coding gain of 0.5 dB for the PR1 channel and 2.4 dB for the PR2 channel at the user bit density, compared with the 16/17 code for the EPR4 channel.

Embedded wavelet-based coding of three-dimensional oceanographic images with land masses

We describe the wavelets around land masses (WAVAL) system for the embedded coding of three-dimensional (3-D) oceanographic images. These images differ from those arising in other applications in that valid data exists only at grid points corresponding to sea. Grid points that cover land or lie beyond the bathymetry have no associated data. For these images, the WAVAL system employs a 3-D lifting wavelet transform tailored specifically to the potentially sparse nature of the data by processing only the valid sea data points between land masses. We introduce successive-approximation runlength (SARL) coding, an embedded-coding procedure that adds successive-approximation properties to the well known stack-run (SR) algorithm. SARL is employed to code wavelet coefficients resulting from the 3-D transform in the WAVAL system. However, it is a general technique applicable to other coding tasks in which embedded coding is desired but for which zerotree techniques are impractical. Experimental results show that the WAVAL system achieves substantial improvement in rate-distortion performance over the technique currently used by the US Navy for compression of oceanographic imagery.

Fault tolerance in computing, compressing, and transmitting FFT data

Remote-sensing applications often calculate the discrete Fourier transform of sampled data and then compress and encode it for transmission to a destination. However, all these operations are executed on computing resources potentially affected by failures. Methods are presented for integrating various fault detection capabilities throughout the data flow path so that the momentary failure of any subsystem will not allow contaminated data to go undetected. New techniques for protecting complete source coding schemes are exemplified by examining a lossy compression system that truncates fast Fourier transform (FFT) coefficients to zero, then compresses the data further by using lossless arithmetic coding. Novel methods protect arithmetic coding computations by internal algorithm checks. The arithmetic encoding and decoding operations and the transmission path are further protected by inserting sparse parity symbols dictated by a high-rate convolutional symbol-based code. This powerful approach introduces limited redundancy at the beginning of the system but performs detection at later stages. While the parity symbols degrade efficiency slightly, the overall compression gain is significant because of the run-length coding. Well-known fault tolerance measures for FFT algorithms are extended to detect errors in the lossy truncation operations, maintaining end-to-end protection. Simulations verify that all single subsystem errors are detected and the overhead costs are reasonable.

A run-length-coding-based approach to stroke extraction of Chinese characters

Traditional stroke extraction approach usually adopts thinning technique as the preprocessing method in obtaining the skeletons of Chinese characters. However, thinning may produce spurious branches and multiple fork points at junctions. Such distortion will make stroke extraction process more complicate and unreliable. This paper proposes a novel run-length-based stroke extraction approach without using the thinning method. Besides, the proposed approach does not need to trace the skeleton pixel by pixel in obtaining the skeletons of Chinese characters. In our approach, run-length coding technique is first employed to get a special skeleton which only owns disjoint line segments without including fork points. Then, an attributed graph is constructed from the skeleton. The attribute between two nodes is determined according to the distance, connectivity and orientation difference between the two corresponding line segments. Intersection relation among line segments is represented by a junction matrix and its associating graph. While stroke extraction is performed, fork points can also be found. Experimental results show that the proposed approach is feasible and efficient in extracting strokes of Chinese characters.

A Single-Chip Video/Audio Codec for Low Bit Rate Application

In this paper, we present a design of video and audio single chip encoder/decoder for portable multimedia application. The single-chip called as video audio signal processor (VASP) consists of a video signal processing block and an audio signal processing block. This chip has mixed hardware/software architecture to combine performance and flexibility. We designed the chip by partitioning between video and audio block. The video signal processing block was designed to implement hardwired solution of pixel input/output, full pixel motion estimation, half pixel motion estimation, discrete cosine transform, quantization, run length coding, host interface, and 16 bits RISC type internal controller. The audio signal processing block is implemented with software solution using a 16 bits fixed point DSP. This chip contains 142,300 gates, 22 kbits FIFO, 107 kbits SRAM, and 556 kbits ROM, and the chip size is 9.02 mm ×9.06 mm which is fabricated using 0.5 micron 3-layer metal CMOS technology.

Medical image compression based on a morphological representation of wavelet coefficients.

Image compression is fundamental to the efficient and cost-effective use of digital medical imaging technology and applications. Wavelet transform techniques currently provide the most promising approach to high-quality image compression which is essential for diagnostic medical applications. A novel approach to image compression based on the wavelet decomposition has been developed which utilizes the shape or morphology of wavelet transform coefficients in the wavelet domain to isolate and retain significant coefficients corresponding to image structure and features. The remaining coefficients are further compressed using a combination of run-length and Huffman coding. The technique has been implemented and applied to full 16 bit medical image data for a range of compression ratios. Objective peak signal-to-noise ratio performance of the compression technique was analyzed. Results indicate that good reconstructed image quality can be achieved at compression ratios of up to 15:1 for the image types studied. This technique represents an effective approach to the compression of diagnostic medical images and is worthy of further, more thorough, evaluation of diagnostic quality and accuracy in a clinical setting.

Matching for Run-Length Encoded Strings

Measuring the similarity between two strings, through such standard measures as Hamming distance, edit distance, and longest common subsequence, is one of the fundamental problems in pattern matching. We consider the problem of finding the longest common subsequence of two strings. A well-known dynamic programming algorithm computes the longest common subsequence of strings X and Y in O(|X|/spl middot/|Y|) time. We develop significantly faster algorithms for a special class of strings which emerge frequently in pattern matching problems. A string S is run-length encoded if it is described as an ordered sequence of pairs (/spl sigma/,i), each consisting of an alphabet symbol /spl sigma/ and an integer i. Each pair corresponds to a run in S consisting of i consecutive occurrences of /spl sigma/. For example, the string aaaabbbbcccabbbbcc can be encoded as a/sup 4/b/sup 4/c/sup 3/a/sup 1/b/sup 4/c/sup 2/. Such a run-length encoded string can be significantly shorter than the expanded string representation. Indeed, runlength coding serves as a popular image compression technique, since many classes of images, such as binary images in facsimile transmission, typically contain large patches of identically-valued pixels.

Fast coding of low-entropy sources

The problem of coding low-entropy information sources is considered. Since the run-length code was offered about 50 years ago by Shannon, it is known that for such sources there exist coding methods much simpler than for sources of a general type. However, known coding methods of low-entropy sources do not reach the given redundancy. In this correspondence, a new method of coding low-entropy sources is offered. It permits a given redundancy r with almost the same encoder and decoder memory size as that obtained by Ryabko (see ibid., vol.40, p.96-9, 1994) for general methods, while encoding and decoding much faster.

4-ary (1,2) run-length limited code for optical storage channels

A 4-ary run-length limited (RLL) code with minimum run-length constraint d = 1 and maximum run-length constraint k = 2 is presented. The proposed code can be represented by a finite state diagram with two states. This is the lowest number of states necessary for representing the code yet presented. A simple docoding rule for the code is also introduced and a scheme for reducing the DC content of the coded sequence in the sense of multilevel running digital sum (RDS) is discussed.

Class of multilevel run-length limited trellis codes

The authors have used a multilevel coding technique to construct run-length limited (RLL) trellis codes with error-correcting capabilities. The constructed codes have better performance than the RLL trellis codes previously proposed, in terms of error-correcting capabilities, coding rates and decoding complexities.

Generalised rate N/(N+1) codes

A generalised construction of rate N/(N+1) run-length limited codes is presented. The (d, k, l, r) constraints are (0, N/4 + 1, N/8, N/8). Encoding and decoding based on the use of multiple pivot bits are described. The encoding and decoding are systematic enough to allow the writing of software to generate efficient logic equations for different N. The logic equations can be further minimised using an automatic synthesis tool.