Past and current optical Earth observation systems designed by CNES are using a fixed-rate data compression processing performed at a high-rate in a pushbroom mode (also called scan-based mode). This process generates fixed-length data to the mass memory and data downlink is performed at a fixed rate too. Because of on-board memory limitations and high data rate processing needs, the rate allocation procedure is performed over a small image area called a "segment". For both PLEIADES compression algorithm and CCSDS Image Data Compression recommendation, this rate allocation is realised by truncating to the desired rate a hierarchical bitstream of coded and quantized wavelet coefficients for each segment. Because the quantisation induced by truncation of the bit planes description is the same for the whole segment, some parts of the segment have a poor image quality. These artefacts generally occur in low energy areas within a segment of higher level of energy. In order to locally correct these ...
TY - JOUR. T1 - A Lightweight Contextual Arithmetic Coder for On-Board Remote Sensing Data Compression. AU - Bartrina-Rapesta,Joan. AU - Blanes,Ian. AU - Aulí-Llinàs,Francesc. AU - Serra-Sagristà,Joan. AU - Sanchez,Victor. AU - Marcellin,Michael W.. PY - 2017/8/1. Y1 - 2017/8/1. N2 - 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 ...
Due to the rapid advancement of automation level for Navys vessels and the staggering data volume generated by advanced sensors/instrumentations, the U.S. Navy is seeking advanced data compression algorithm and bandwidth utilization mechanism that will enable very large amounts of data to be transmitted in bandwidth-limited scenarios from ship to shore. In order to meet the Navys design requirements, Broadata Communications, Inc. (BCI) proposes an Advanced Lossless Inter-channel Data Compression with Enhanced TCP/IP (ADET) capability, based on our extensive experience in data processing, compression, and bandwidth efficient transmissions. The proposed ADET efficiently integrates our two novel innovations-highly efficient lossless inter-channel compression and bandwidth efficient TCP/IP-into an offload engine. This engine not only achieves superior compression performance but also provides robust and bandwidth-efficient data delivery over dynamic and bandwidth-limited tactical networks. Based ...
Universal and Accessible Entropy Estimation Using a Compression Algorithm Entropy and free-energy estimation are key in thermodynamic characterization of...
This article provides an implementation of the LZW compression algorithm in Java; Author: fahadkhowaja; Updated: 13 Aug 2006; Section: Java; Chapter: Languages; Updated: 13 Aug 2006
This article provides an implementation of the LZW compression algorithm in Java; Author: fahadkhowaja; Updated: 13 Aug 2006; Section: Java; Chapter: Languages; Updated: 13 Aug 2006
0003] Perceptually Lossless Color Compression is desirable in the field of digital imaging, in particular, with application to improved performance of network and mobile imaging devices. Conventional systems provide either lossy or lossless compression, neither of these modes being adequate for most digital imaging or remote capture applications. Lossless compression in colorspace generates very large file sizes, unsuitable for distributed databases and other applications where transmission or hosting size is a factor. Lossy compression assumes an implicit tradeoff between bitrate and distortion so that the higher the compression, the greater the level of distortion. One example conventional compression method is MRC compression. (See Mixed Raster Content (MRC) Model for Compound Image Compression, Ricardo de Queiroz et al., Corporate Research & Technology, Xerox Corp., available at http://image.unb.br/queiroz/papers/ei99mrc.pdf, and see U.S. Pat. No. 7,110,137, the entire disclosures of which ...
TY - JOUR. T1 - Regression Wavelet Analysis for Near-Lossless Remote Sensing Data Compression. AU - Alvarez-Cortes, Sara. AU - Serra-Sagrista, Joan. AU - Bartrina-Rapesta, Joan. AU - Marcellin, Michael W.. PY - 2020/2. Y1 - 2020/2. N2 - Regression wavelet analysis (RWA) is one of the current state-of-the-art lossless compression techniques for remote sensing data. This article presents the first regression-based near-lossless compression method. It is built upon RWA, a quantizer, and a feedback loop to compensate the quantization error. Our near-lossless RWA (NLRWA) proposal can be followed by any entropy coding technique. Here, the NLRWA is coupled with a bitplane-based coder that supports progressive decoding. This successfully enables gradual quality refinement and lossless and near-lossless recovery. A smart strategy for selecting the NLRWA quantization steps is also included. Experimental results show that the proposed scheme outperforms the state-of-the-art lossless and the near-lossless ...
Satellite data compression has been an important subject since the beginning of satellites in orbit, and it has become an even more active research topic. Following technological advancements, the trend of new satellites has led to an increase in spatial, spectral, and radiometric resolution, an extension in wavelength range, and a widening of ground swath to better serve the needs of the user community and decision makers. Data compression is often used as a sound solution to overcome the challenges of handling a tremendous amount of data. I have been working in this area since I was pursing my Ph. D. thesis almost 30 years ago.. Over the last two decades, I - as a senior research scientist and technical authority with the Canadian Space Agency - have led and carried out research and development of innovative data compression technology for optical satellites in collaboration with my colleagues at the agency, other government departments, my postdoctoral visiting fellows, internship students, ...
Get Data Compression Techniques Homework Help, Data Compression Techniques Project Help and Dissertation help by Tutorspoint experts
Video compression has one chief goal in mind - to reduce the file size of uncompressed video without affecting the quality of the video itself. Video compression was important in the days when the chief delivery medium was CD or DVD. Nowadays as the Internet becomes the preferred medium for video sharing, its important that video needs to be compressed in such a manner so that uploading and downloading time is greatly reduced. Heres an overview of what video compression is all about.
Data compression in GIS refers to the compression of geospatial data so that the volume of data transmitted across networks can be reduced. A properly choosen compression algorithm can reduce data size upto 5 - 10% of the original image and 10 - 20% for vector and text data. Such compression ratios could result in significant performance improvement ...
An image information compressing method for densely compressing image information, in particular, dynamic image information, a compressed image information recording medium for recording compressed image information, and a compressed image information reproducing apparatus capable of reproducing compressed image information at high speed in a short time are provided. Each image frame constituting a dynamic image information is divided into key frames and movement compensation frames. The key frame is divided into blocks so that an image pattern of each block is vector-quantized by using a algorithm of the Kohonens self-organizing featured mapping. The movement compensation frame is processed such that a movement vector for each block is determined and a movement vector pattern constituting a large block is vector-quantized by using the algorithm of the Kohonens self-organizing featured mapping. The compressed image information recording medium includes an index recording region for recording the
The preferred embodiment includes a method and system for processing ultrasound data during or after compression. Various compression algorithms, such as JPEG compression, are used to transfer ultrasound data. The ultrasound data may include image (i.e. video data) or data obtained prior to scan conversion, such as detected acoustic line data or data complex in form. Compression algorithms typically include a plurality of steps to transform and quantize the ultrasound data. Various processes in addition to compression may be performed as part of one or more of the compression steps. Furthermore, various ultrasound system processes typically performed on uncompressed ultrasound data may be performed using compressed or partially compressed ultrasound data. Operation on compressed or partially compressed data may more efficiently provide processed data for generation of an image. Fewer operations are required by one or more processors when operating on compressed or partially compressed data than for
A universal data compression algorithm is described which is capable of compressing long strings generated by a finitely generated source, with a near op
This paper presents a technical review for enhancing security and reliability in the transmission of information. In this paper Watermarking technique along with Data Compression is being described to improve the quality, security and efficiency in the transmission of information. In this paper we provide a measure to remove the problem of data redundancy and security by combining the two techniques. Watermarking is an valuable technique being invented to prevent any malicious use of our data. Using Haar Transform and Wavelet Concept we implement watermarking code and watermark all the images of our concern. Then by applying the data compression technique we transmit our information which is more secure then in raw form. So in this way we are enhancing the data security in Multimedia Transmission.
A method for encoding compressed graphics video information and decoding such information. The method consists of enriching the video information in zeros through shifting and Exclusive ORing video with itself. A number of methods are attempted in the shifting and Exclusive ORing process in order to determine the method which yields the optimum zero enriched image. The zero enriched image is then encoded and the encoded information stored. Upon retrieval, the information is decoded and an Exclusive OR and shifting process is done to obtain the original video information.
The |i|Journal of Electronic Imaging|/i| (JEI), copublished bimonthly with the Society for Imaging Science and Technology, publishes peer-reviewed papers that cover research and applications in all areas of electronic imaging science and technology.
Data Compression Definition - Data compression is the process of modifying, encoding or converting the bits structure of data in such a way that it...
The relationship between prediction and data compression can be extended to universal prediction schemes and universal data compression. Previous work show
alphadogg writes Google is open-sourcing a new general purpose data compression library called Zopfli that can be used to speed up Web downloads. The Zopfli Compression Algorithm, which got its name from a Swiss bread recipe, is an implementation of the Deflate compression algorithm that creates a ...
The databases of genomic sequences are growing at an explicative rate because of the increasing growth of living organisms. Compressing deoxyribonucleic acid (DNA) sequences is a momentous task as the databases are getting closest to its threshold. Various compression algorithms are developed for DNA sequence compression. An efficient DNA compression algorithm that works on both repetitive and non-repetitive sequences known as HuffBit Compress is based on the concept of Extended Binary Tree. In this paper, here is proposed and developed a modified version of HuffBit Compress algorithm to compress and decompress DNA sequences using the R language which will always give the Best Case of the compression ratio but it uses extra 6 bits to compress than best case of HuffBit Compress algorithm and can be named as the Modified HuffBit Compress Algorithm ...
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): A universal algorithm for sequential data compression is presented. Its performance is investigated with respect to a nonprobabilistic model of constrained sources. The compression ratio achieved by the proposed universal code uniformly approaches the lower bounds on the compression ratios attainable by block-to-variable codes and variable-to-block codes designed to match a completely specified source.
So, when I try to compress the compressed version of War and Peace, I get a result thats 0.3% larger. In other words, the compressed version of War and Peace fails the Dembski criterion. Obviously, compression cannot always be iterated successfully, or wed compress every finite text to nothing. But my WarAndPeace.compressed file is just as much the product of intelligent design as WarAndPeace.txt. In fact, it is the product of a greater amount of design: there is Tolstoys authorship, and there is the Julian Sewards design of the bzip2 algorithm.. Now, could there be an algorithm that could compress my WarAndPeace.compressed file? No doubt. For instance, I could decompress it with bunzip and then apply a more efficient compression algorithm, like LZMA. However, there is a limit to this approach.. ...
Colombo JN, Seckeler MD, Barber BJ, Krupinski EA, Weinstein RS, Sisk D, and Lax D. Application and Utility of iPads in Pediatric Tele-echocardiography. (2016). Telemedicine and e-Health, May 2016, 22(5): 1-5. doi: 10.1089/tmj 2015.0114. ...
To determine what information in an audio signal is perceptually irrelevant, most lossy compression algorithms use transforms such as the modified discrete cosine transform (MDCT) to convert time domain sampled waveforms into a transform domain. Once transformed, typically into the frequency domain, component frequencies can be allocated bits according to how audible they are. Audibility of spectral components calculated using the absolute threshold of hearing and the principles of simultaneous masking-the phenomenon wherein a signal is masked by another signal separated by frequency-and, in some cases, temporal masking-where a signal is masked by another signal separated by time. Equal-loudness contours may also be used to weight the perceptual importance of components. Models of the human ear-brain combination incorporating such effects are often called psychoacoustic models.[25] Other types of lossy compressors, such as the linear predictive coding (LPC) used with speech, are source-based ...
To determine what information in an audio signal is perceptually irrelevant, most lossy compression algorithms use transforms such as the modified discrete cosine transform (MDCT) to convert time domain sampled waveforms into a transform domain. Once transformed, typically into the frequency domain, component frequencies can be allocated bits according to how audible they are. Audibility of spectral components calculated using the absolute threshold of hearing and the principles of simultaneous masking-the phenomenon wherein a signal is masked by another signal separated by frequency-and, in some cases, temporal masking-where a signal is masked by another signal separated by time. Equal-loudness contours may also be used to weight the perceptual importance of components. Models of the human ear-brain combination incorporating such effects are often called psychoacoustic models.[23] Other types of lossy compressors, such as the linear predictive coding (LPC) used with speech, are source-based ...
A three-dimensional (3-D) image-compression algorithm based on integer wavelet transforms and zerotree coding is presented. The embedded coding of zerotrees of wavelet coefficients (EZW) algorithm is extended to three dimensions, and context-based adaptive arithmetic coding is used to improve its performance. The resultant algorithm, 3-D CB-EZW, efficiently encodes 3-D image data by the exploitation of the dependencies in all dimensions, while enabling lossy and lossless decompression from the same bit stream. Compared with the best available two-dimensional lossless compression techniques, the 3-D CB-EZW algorithm produced averages of 22%, 25%, and 20% decreases in compressed file sizes for computed tomography, magnetic resonance, and Airborne Visible Infrared Imaging Spectrometer images, respectively. The progressive performance of the algorithm is also compared with other lossy progressive-coding algorithms.. © 2000 Optical Society of America. Full Article , PDF Article ...
1. A data compression method comprising: a first step of extracting a repeated character string appearing more than twice among character strings included in original data; a second step of calculating a Hash value of the extracted repeated character string, storing the Hash value in a dictionary table, encoding the repeated character string and storing the encoded character string in compressed data; a third step of encoding character strings other than the repeated character string included in the original data according to LZ77 (Lempel-Ziv 77) algorithm and storing the encoded character strings in the compressed data; and a fourth step of calculating the probability of appearance of a specific character after a previous character in the encoding operation of the third step and storing the probability in the compressed data, wherein the fourth step comprises the steps of: calculating the probability of appearance of a specific character after a single specific character and storing the ...
Anyone whos used a mobile for voice calls may have noticed that the background noise often sounds like speech or chirps. The characteristics of speech presumably have some features in common with birdsong and others not, and speech compression is presumably optimised for speech. However, there are other species which produce sounds somewhat speech-like but not identical, for instance birdsong, whale song and sounds made by other primates. Other species make more regular sounds, for instance cicadas and crickets.. So, my idea is this: find a method of sound compression which is lossy but optimised for species. It falls into two parts. One exploits characteristics common to all sound produced by animals, from cicadas to cockerels. The other is tweaked according to the species, the aim being to produce an output which the species concerned cant distinguish from the real thing, with the option of choosing compression optimised just for that species or for two different species. This would be ...
The bane of my existence. Its a tool to compress textures. Unity uses it to compress PVR/ETC1/ETC2 textures and it takes 34264564368245634 years to...
Turk: People do use them and there are circumstances under which that works. Potential problems or reasons to use BR instead. Some reasons are geographical. Rural Minnesota w/intermittent broadband. HD downloads are beyond my ability. Being able to get Blu-Ray is useful. The other thing is that HD and BR are not actually the same thing in the way theyre encoded. Different compression algorithms. BR comes on a disc and theres no need to download-BR holds a very large amount of data. Download is encoded to produce a smaller file. If you look at the relative size of 720p versus 1080HD download is not as different as youd expect given 2 ½ more pixels. The reason is that video is encoded using any of a variety of codecs. There are three different codecs BR supports. Each has multiple options for compression algorithms. What is the bitrate? Variable bitrate: if a scene doesnt have a lot of motion, bitrate is lower-allows better distribution of the data. Different algorithms serve different ...
Turk: People do use them and there are circumstances under which that works. Potential problems or reasons to use BR instead. Some reasons are geographical. Rural Minnesota w/intermittent broadband. HD downloads are beyond my ability. Being able to get Blu-Ray is useful. The other thing is that HD and BR are not actually the same thing in the way theyre encoded. Different compression algorithms. BR comes on a disc and theres no need to download-BR holds a very large amount of data. Download is encoded to produce a smaller file. If you look at the relative size of 720p versus 1080HD download is not as different as youd expect given 2 ½ more pixels. The reason is that video is encoded using any of a variety of codecs. There are three different codecs BR supports. Each has multiple options for compression algorithms. What is the bitrate? Variable bitrate: if a scene doesnt have a lot of motion, bitrate is lower-allows better distribution of the data. Different algorithms serve different ...
This paper presents a set of full-resolution lossy image compression methods based on neural networks. Each of the architectures we describe can provide variable compression rates during deployment without requiring retraining of the network: each network need only be trained once. All of our architectures consist of a recurrent neural network (RNN)-based encoder and decoder, a binarizer, and a neural network for entropy coding. We compare RNN types (LSTM, associative LSTM) and introduce a new hybrid of GRU and ResNet. We also study "one-shot" versus additive reconstruction architectures and introduce a new scaled-additive framework. We compare to previous work, showing improvements of 4.3%-8.8% AUC (area under the rate-distortion curve), depending on the perceptual metric used. As far as we know, this is the first neural network architecture that is able to outperform JPEG at image compression across most bitrates on the rate-distortion curve on the Kodak dataset images, with and without the ...
Lossless text data compression is an important field as it significantly reduces storage requirement and communication cost. In this work, the focus is directed mainly to different file compression coding techniques and comparisons between them. Some memory efficient encoding schemes are analyzed and implemented in this work. They are: Shannon Fano Coding, Huffman Coding, Repeated Huffman Coding and Run-Length coding. A new algorithm
The rapid development of high throughput sequencing (HTS) technologies has made a considerable impact on clinical and genomics research. These technologies offer a time-efficient and cost-effective means for genotyping many pharmaceutical genes affecting the drug response (also known as ADMER genes), which makes HTS a good candidate for assisting the drug treatment and dosage decisions. However, challenges like data storage and transfer, as well as accurate genotype inference in the presence of various structural variations, are still preventing the wider integration of HTS platforms in clinical environments. For these reasons, this thesis presents fast and efficient methods for HTS data compression and accurate ADMER genotyping.First we propose a novel compression technique for reference-aligned HTS data, which utilizes the local assembly technique to assemble the donor genome and eliminate the redundant information about the donor present in the HTS data. Our results show that we can achieve ...
Data compression and decompression methods for compressing and decompressing data based on an actual or expected throughput (bandwidth) of a system. In one embodiment, a controller tracks and monitors the throughput (data storage and retrieval) of a data compression system and generates control signals to enable/disable different compression algorithms when, e.g., a bottleneck occurs so as to increase the throughput and eliminate the bottleneck.
Nowadays, a variety of data-compressors (or archivers) is available, each of which has its merits, and it is impossible to single out the best ones. Thus, one faces the problem of choosing the best method to compress a given file, and this problem is more important the larger is the file. It seems natural to try all the compressors and then choose the one that gives the shortest compressed file, then transfer (or store) the index number of the best compressor (it requires log m bits, if m is the number of compressors available) and the compressed file. The only problem is the time, which essentially increases due to the need to compress the file m times (in order to find the best compressor). We suggest a method of data compression whose performance is close to optimal, but for which the extra time needed is relatively small: the ratio of this extra time and the total time of calculation can be limited, in an asymptotic manner, by an arbitrary positive constant. In short, the main idea of the
The newest iteration is now more capable: attackers using the optimised BREACH (Browser Reconnaissance and Exfiltration via Adaptive Compression of Hypertext) can target noisy end-points that use sluggish block ciphers, including AES 128 bit.. They say its also 500 times faster than the original attack; browser parallelisation is sped up by a factor of six, while requests are now 16 times faster.. The original BREACH was released to much acclaim at Black Hat in 2013, and attacks the common Deflate data compression algorithm used to save bandwidth in web communications.. The original version was itself an expansion of CRIME (Compression Ratio Info-leak Made Easy), an exploit that turned compression of encrypted web requests against users.. Karakostas and Zindros (@dionyziz) of the National Technical University of Athens and the University of Athens have described their work in the paper Practical New Developments on BREACH [PDF].. On stage, they showed security delegates how the attack could be ...
Our data compression technology is very useful when unable to send the data captured from field to server due to lack of network can be compressed and stored in the mobile and later send to server upon reaching network area automatically. The compression technology uses a unique proprietary intelligent i-Compression technology to compress data to its minimal size. Using this technology the data can be stored on mobile phone for a period of 15 days ...
modapi writes StorageMojo is reporting that a company at Storage Networking World in San Diego has made a startling claim of 25x data compression for digital data storage. A combination of de-duplication and calculating and storing only the changes between similar byte streams is apparently the key...
Data Compression is feature of Microsoft SQL Server to reduce the size of table on the basis of Duplicates, Null & Zeroes. Its a process of reducing size of database & its objects by increasing CPU cycle and reducing I/O effort.. ...
Compressive Genomics. The key to finding a solution is to notice that most genomicsequences differ by very little. It may well be that the number of complete genome sequences being stored is increasing rapidly, but the actual amount of new data is very small. In other words, a single DNA sequence isnt particular.... Tags: data compression, genomics, sequencing, redundancy, repeats, bam, sff, gz, zip. ...
Logos Verlag Berlin, Germany, Andreas Bartels Data Compression and Compressed Sensing in Imaging Mass Spectrometry and Sporadic Communication
General purpose data compression routines tend to be used on binary streams of data, either from files or in-memory objects. So what is the best general paradigm for input and output when compressing data: iostreams or iterator?
Hi All, If youre using a mobile connection on your boat try the Opera Mini mobile data compression browser with add- blocker, just updated today . I
Excellent results obtained from over 600 neonatal sessions using ViTel Nets MedVizer tele-echocardiography product, establishes ViTel Nets technology as a solution for improved cardiac care for sick children. Dr. Craig Sable stated: "With the MedVizer tele-echocardiography product, we have a tool which lets us be there to help. The value of this system is exceeding our expectations for improved care of the children we serve.". The paediatric version of ViTel Nets MedVizer tele-echocardiography system was designed in collaboration with paediatric cardiologists practising at CNMC and has demonstrated its effectiveness for paediatric applications over the past three years. More than 600 telemedicine transmissions have been performed in the first three years of the programme. Currently, there are ten to twelve telemedicine transmissions each week. Subsequent review of the videotape copy confirmed the telemedicine diagnosis in all cases.. Dr. Sable presented the results of his telemedicine study ...
Lossless MP3 Song by Kohoutek from the album Lossless Loss (2-Track Single). Download Lossless song on Gaana.com and listen offline.
Many air traffic and maritime radio channels, like 2182 kHz and VHF 16, are being monitored and continuously recorded by numerous vessels and ground stations. Even though gigabytes are now cheap, long recordings would have to be compressed to make them easier to move around.. There are some reasons not to use lossy compression schemes like MP3 or Vorbis. Firstly, radio recordings are used in accident investigations, and additional artifacts at critical moments could hinder investigation. Secondly, lossy compression performs poorly on noisy signals, because of the amount of entropy present. Lets examine some properties of such recordings that may aid in their lossless compression instead.. A common property of radio conversations is that the transmissions are short, and theyre followed by sometimes very long pauses. Receivers often silence themselves in the absence of a carrier (known as squelching), so theres nothing interesting to record during that time.. This can be exploited by ...
Many air traffic and maritime radio channels, like 2182 kHz and VHF 16, are being monitored and continuously recorded by numerous vessels and ground stations. Even though gigabytes are now cheap, long recordings would have to be compressed to make them easier to move around.. There are some reasons not to use lossy compression schemes like MP3 or Vorbis. Firstly, radio recordings are used in accident investigations, and additional artifacts at critical moments could hinder investigation. Secondly, lossy compression performs poorly on noisy signals, because of the amount of entropy present. Lets examine some properties of such recordings that may aid in their lossless compression instead.. A common property of radio conversations is that the transmissions are short, and theyre followed by sometimes very long pauses. Receivers often silence themselves in the absence of a carrier (known as squelching), so theres nothing interesting to record during that time.. This can be exploited by ...