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.

Lossy Image Compression Using Multiwavelet Transform for Wireless Transmission

Abstract: The performance of the wavelets within the field of image process is standard. Multiwavelets is the next step in riffle theory and it takes the performance of wavelets to the next level. In this work the performance of the Integer Multiwavelet transform (IMWT) for lossy compression has been studied. The Proposed IMWT shows sensible performance in lossy reconstruction of the images than that of Existing lossy reconstruction. This work utilizes the performance of the Proposed IMWT for lossy compression of images with encoding techniques like Magnitude set coding and Run Length Encoding. The transform coefficients are unit coded by means of Magnitude set coding and run length coding techniques which in turn results with low bits. The transform coefficient matrix is coded on not taking under consideration of the sign values using the Magnitude Set--Variable Length Integer illustration. The sign data of the coefficients is coded as bit plane with zero thresholds. This Bit plane may be used as it is or coded to scale back the bits per pixels. The Simulation was exhausted using Matlab.

Data-modifying run length encoder to avoid data expansion

Abstract: A method of selectively run length encoding data may include removing a trigger value from one or more data elements if the trigger value is present in the one or more data elements and calculating a run length of the one or more data elements. The method may also include encoding the one or more data elements as a command pair when the run length is greater than two. The command pair may include the trigger value. The one or more data elements may be output without encoding the one or more data elements when the run length is not greater than two.

Comp-bit-list size improvement in mespotine rle and its applications

Abstract: Run Length Encoding (RLE) is one of the simplest and primitive lossless data compression technique. RLE sometimes doubles the size of compressed data stream. To overcome this disadvantage, several algorithms have been introduced, one of which being Mespotine RLE (MRLE). This paper introduces modification to MRLE technique in which the constant size ‘Comp-Bit List’ have been replaced by ‘Variable Size Comp-Bit List’ and refers to the new technique as improved – MRLE (iMRLE) technique. This paper discusses the details of ‘Variable Size Comp-Bit List’ and utilizes this concept for lossless compression and decompression of 8-bit grayscale medical images and extends the concept to 16-bit grayscale medical images. Image quality metrics such as Compression Ratio (CR), Root Mean Square Error (RMSE), Peak Signal-to-Noise Ratio (PSNR) and Entropy are used to check the quality of decompressed image obtained using iMRLE technique. Finally, the compression ratio achieved for existing MRLE and iMRLE techniques for 8-bit and 16-bit grayscale images have been assessed and iMRLE is found to produce best results for lossless compression and decompression of medical images

Streaming sorting network based BWT acceleration on FPGA for lossless compression

Abstract: The Burrows-Wheeler Transform (BWT) has received special attention due to its effectiveness in lossless data compression algorithms Because BWT is a time-consuming task, the efficient hardware accelerator that can yield high throughputs is required in real-time applications This paper presents a novel BWT accelerator based on the streaming sorting network The streaming sorting network performs the suffix sorting of large amount of data which is the most difficult task in BWT Our BWT accelerator is implemented on a NetFPGA board Experimental results show that it achieves 143X speedup compared with the state-of-art work when the data block size is 4KB Furthermore, we design and implement a lossless data compression system based on the proposed BWT accelerator The hardware system is composed of Burrows-Wheeler Transform module, the move-to-front encoding module, the run length encoding module, and the canonical Huffman encoding module We evaluate the system performance on a NetFPGA board at the frequency of 155MHz The throughput of the system could reach 179 MB/s on board when we use only one streaming sorting network for a 4KB block The system throughput can be linearly improved up to 537 MB/s in simulation on a Virtex UltraScale xcvu440 chip if we use three streaming sorting networks to compute BWT