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Run-length encoding

About: Run-length encoding is a research topic. Over the lifetime, 504 publications have been published within this topic receiving 4441 citations. The topic is also known as: RLE.


Papers
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01 Jan 2014
TL;DR: A near lossless image compression algorithm based on row by row classifier with encoding schemes like Lempel Ziv Welch (LZW), Huffman and Run Length Encoding (RLE) on color images is proposed, which reveals that the proposed algorithm have smaller bits per pixel (bpp) than simple LZW, HuffMan and RLE encoding techniques.
Abstract: Lossless image compression is needed in many fields like medical imaging, telemetry, geophysics, remote sensing and other applications, which require exact replica of original image and loss of information is not tolerable. In this paper, a near lossless image compression algorithm based on row by row classifier with encoding schemes like Lempel Ziv Welch (LZW), Huffman and Run Length Encoding (RLE) on color images is proposed. The algorithm divides the image into three parts R, G and B, apply row by row classification on each part and result of this classification is records in the mask image. After classification the image data is decomposed into two sequences each for R, G and B and mask image is hidden in them. These sequences are encoded using different encoding schemes like LZW, Huffman and RLE. An exhaustive comparative analysis is performed to evaluate these techniques, which reveals that the proposed algorithm have smaller bits per pixel (bpp) than simple LZW, Huffman and RLE encoding techniques.
Patent
07 May 2020
TL;DR: In this article, the authors present a data processing method for running length encoding for source data in which unit data is serially connected by a computing device, which consists of: dividing the source data into a plurality of blocks, adjusting the reading order of the source source data such that unit data having the same relative offset in a block are sequentially arranged while sequentially moving each of the divided blocks.
Abstract: Provided is a data compressing method efficiently compressing run length encoding by adjusting a reading order for source data. According to one embodiment of the present invention, the data processing method, which is a method compressing run length encoding for source data in which unit data is serially connected by a computing device, comprises the steps of: dividing the source data into a plurality of blocks; adjusting the reading order of the source data such that unit data having the same relative offset in a block are sequentially arranged while sequentially moving each of the divided blocks; and compressing the source data by running length encoding by sequentially reading the unit data in accordance with the adjusted order.
01 Jan 2008
TL;DR: To decrease size of data under transmission a new algorithm, namely RLE-BER (Run Length Encoding with Binary Encoded Runs) for radar images compression is proposed, and initial results are very promising, as the average compression ratio is near to 5: 1 when considering monochromepalette (binary image).
Abstract: One of the most important issue in maritime international transport is the necessity of increasing the level ofsafe in vessel's navigation. We can achieve this goal using various methods. One ofthem is the enlargementand enrichment of navigational data processed by own deck computer net and external systems AIS (Automatic Identification System) and VTS (Vessel Traffic Service). The radar image contains ex­ tensive and useful navigational information. That is why the incorporation of it into remote transmission is proposed here. In order to successfully realize this process the en­ hancement of the NMEA (National Marine Electronics As­ sociation) code is proposed through incorporation ofradar images into particular protocols. To decrease size of data under transmission a new algorithm, namely RLE-BER (Run Length Encoding with Binary Encoded Runs) for radar images compression is proposed Some experimental results are presented on real data. The detail description of the method is also provided The initial results are very promising, as the average compression ratio is near to 5: 1 when considering monochromepalette (binary image). The proposedmethod is lossless, because we assumed the maxi­ mum safety level ofthe final system.
Journal ArticleDOI
TL;DR: Experimental results show that the algorithm is effective in compressing data, effectively reducing the size of data storage and speeding up the transmission of background data, so it has very good application value.
Abstract: Aiming at the problem of data transmission in distributed framework of web project, a compression algorithm combining Huffman encoding and Run length encoding is used to compress data in this paper, thus reducing the amount of data and improving the speed of data transmission. The integrity of data can be guaranteed since lossless compression is used. Experimental results show that the algorithm is effective in compressing data, effectively reducing the size of data storage and speeding up the transmission of background data, so it has very good application value.
Patent
18 Mar 2015
TL;DR: In this paper, a page dot matrix self-adaptive compression method and device is presented. But the method is not suitable for VDP work, as it requires page-based encoding and run-length encoding.
Abstract: The invention discloses a page dot matrix self-adaptive compression method and device The method comprises the steps that page dot matrix data in VDP work are acquired with a page acting as a unit; the page dot matrix data are compressed in turn and compression ratio of each page is recorded; and a compression mode is dynamically regulated according to compression ratio, and the compression mode comprises a previous-page-based encoding compression mode and a run length encoding compression mode The invention also discloses a page dot matrix self-adaptive reduction method and device With application of the method, decompression efficiency can be enhanced
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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202123
202020
201920
201828
201727
201624