Topic
Lempel–Ziv–Markov chain algorithm
About: Lempel–Ziv–Markov chain algorithm is a research topic. Over the lifetime, 6 publications have been published within this topic receiving 41 citations. The topic is also known as: LZMA & Lempel–Ziv–Markov algorithm.
Papers
TL;DR: This article introduces a highly reliable and low-complexity image compression scheme using neighborhood correlation sequence (NCS) algorithm that increases the compression performance and decreases the energy utilization of the sensor nodes with high fidelity.
Abstract: Recently, the advancements in the field of wireless technologies and micro-electro-mechanical systems lead to the development of potential applications in wireless sensor networks (WSNs). The visual sensors in WSN create a significant impact on computer vision based applications such as pattern recognition and image restoration. generate a massive quantity of multimedia data. Since transmission of images consumes more computational resources, various image compression techniques have been proposed. But, most of the existing image compression techniques are not applicable for sensor nodes due to its limitations on energy, bandwidth, memory, and processing capabilities. In this article, we introduce a highly reliable and low-complexity image compression scheme using neighborhood correlation sequence (NCS) algorithm. The NCS algorithm performs the bit reduction operation and then encoded by a codec (such as PPM, Deflate, and Lempel Ziv Markov chain algorithm.) to further compress the image. The proposed NCS algorithm increases the compression performance and decreases the energy utilization of the sensor nodes with high fidelity. Moreover, it achieved a minimum end to end delay of 1074.46 ms at the average bit rate of 4.40 bpp and peak signal to noise ratio of 48.06 on the applied test images. On comparing with state-of-art methods, the proposed method maintains a better tradeoff between compression efficiency and reconstructed image quality.
93 citations
29 Mar 2018
TL;DR: The existing image compression techniques such as Lempel Ziv Markov chain Algorithm (LZMA), Burrows Wheeler Transform (BWT), LempelZiv Welch (LW) coding, Deflate and LZ77 are compared to one another and results imply that LZMA achieve better compression than other methods with the compression ratio, compression factor and compression time.
Abstract: Satellite images are larger in size and it needs high amount of storage space and transmission time. There is a greater challenge to store or transmit the satellite images from the satellite to earth station. Image compression techniques have evolved to effectively process the images with tolerable or no loss in quality. The satellite images can be compressed to manage the storage space and communication bandwidth. Though several researches have been done on compression of natural images, only few have concentrated on satellite images. The nature of satellite images poses a greater challenge to compress satellite images. To carry out this work, we have used a satellite image dataset which consists of 2800 images of ships in satellite imagery with ship or no-ship classification. The existing image compression techniques such as Lempel Ziv Markov chain Algorithm (LZMA), Burrows Wheeler Transform (BWT), Lempel Ziv Welch (LZW) coding, Deflate and LZ77 are compared to one another. The comparison results imply that LZMA achieve better compression than other methods with the compression ratio, compression factor and compression time of 0.5666, 1.765 and 53 seconds respectively.
5 citations
22 Aug 2007
TL;DR: The experiment results indicate that the compression ratio of the proposed new algorithm for the Result Drawings with cgm format is larger than currently popular compression software.
Abstract: Since the data of Well Logging Result Drawings is so large, it is necessary to apply efficient algorithm to compress them. Based on the lossless compression of LZMA (Lempel-Ziv-Markov chain-Algorithm), this paper presents a new compressing algorithm for Well Logging Result Drawings after analyzing Result Drawings in CGM (Computer Graphics Metafile) format. The experiment results indicate that the compression ratio of the proposed new algorithm for the Result Drawings with cgm format is larger than currently popular compression software. The new algorithm is also suitable to compress Result Drawings in any other vector format.
4 citations
1 Jan 2011
2 citations
1 Mar 2018
TL;DR: The comparison results imply that PPM, LZW and Deflate64 achieve better compression than other methods, at the same time, Deflate and LZ77 achieves negative compression where the value of compression ratio crosses one.
Abstract: The amount of data transmission especially images over internet are rapidly increasing day by day. The effective lossless image compression becomes a greater challenge now than ever. The efficiently compressed images can be useful to remotely access multimedia file at a faster rate with lesser burden on network infrastructure. Though numerous researches has been done on compression of Continuous Tone (CT) images, only few has concentrated on Discrete Tone (DT) images. The nature of CT and DT images are contrast to each other. In this study, the existing image compression techniques are applied to DT images and the results are analyzed. To carry out his work, we have collected an own DT image dataset which consists of 11 reference images with its several distorted versions. The dataset contains a total of 71 images and the existing image compression techniques such as Lempel Ziv Markov chain Algorithm (LZMA), Prediction by Partial Matching (PPM), Burrows Wheeler Transform (BWT), Lempel Ziv Welch (LZW) coding, Deflate, LZ77 and Deflate64. The comparison results imply that PPM, LZW and Deflate64 achieve better compression than other methods. At the same time, Deflate and LZ77 achieves negative compression where the value of compression ratio crosses one.
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2020 | 1 |
| 2019 | 1 |
| 2018 | 2 |
| 2011 | 1 |
| 2007 | 1 |