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.

Lossless Text Image Compression using Two Dimensional Run Length Encoding

Abstract: Text images are used in many types of conventional data communication where texts are not directly represented by digital character such as ASCII but represented by an image, for instance facsimile file or scanned documents. We propose a combination of Run Length Encoding (RLE) and Huffman coding for two dimensional binary image compression namely 2DRLE. Firstly, each row in an image is read sequentially. Each consecutive recurring row is kept once and the number of occurrences is stored. Secondly, the same procedure is performed column-wise to the image produced by the first stage to obtain an image without consecutive recurring row and column. The image from the last stage is then compressed using Huffman coding. The experiment shows that the 2DRLE achieves a higher compression ratio than conventional Huffman coding for image by achieving more than 8:1 of compression ratio without any distortion.

Wavelet-Based Compression and Peak Detection Method for the Experimentally Estimation of Microtubules Dynamic Instability Parameters Identified in Three States

Abstract: Recent studies has revealed that Microtubules (MTs) exhibit three transition states of growth, shrinkage and pause. In this paper, we first introduce a three states random evolution model as a framework for studying MTs dynamics in three transition states of growth, pause and shrinkage. Then, we introduce a non-traditional stack run encoding scheme with 5 symbols for detecting transition states as well as to encode MT experimental data. The peak detection is carried out in the wavelet domain to effectively detect these three transition states. One of the added advantages of including peak information while encoding being that it enables to detect the peaks efficiently and encodes them simultaneously in the wavelet domain without having the need to do further processing after the decoding stage. Experimental results show that using this form of non-traditional stack run encoding has better compression and reconstruction performance as opposed to traditional stack run encoding and run length encoding schemes. Parameters for MTs modeled in the three states are estimated and is shown to closely approximate original MT data for lower compression rates. As the compression rate increases, we may end up throwing away details that are required to detect transition states of MTs. Thus, choosing the right compression rate is a trade-off between admissible level of error in signal reconstruction, its parameter estimation and considerable rate of compression of MT data.

Image Compression using Shannon-Fano-Elias Coding and Run Length Encoding

Abstract: Image Compression is a technique, which reduces the size of an image without much loss of information. In this paper we have put forward a new method for image compression that includes techniques such as Shannon-Fano - Elias coding followed by Run Length Encoding (RLE). By using parameters like Peak Signal to Noise Ratio(PSNR), Mean Square Error (MSE) the efficiency of our proposed algorithm is evaluated by giving square matrix image (256×256) as input.

Compression for DNA Sequences Using Huffman Encoding

Abstract: Over the last two decades, the DNA sequence handling and storing problem has been considered as a big problem for many bioinformatics researchers because genomic databases are increasing drastically. To handle this problem, computational biology plays an important role, such as searching for homology, genome formulation, predicting for a new protein sequence, hereditary control networks, and new creative genomics structure. Available resources are not sufficient for storing and handling large DNA sequences. There are various tools developed by using different algorithms and approach. We have proposed an algorithm to improve the compression ratio which uses the concept of RLE (run length encoding) with a Modified HuffBit algorithm. The results obtained by the proposed method are found to be 20% more accurate when compared to existing algorithms.

TRLE - an efficient data compression scheme for image composition of parallel volume rendering systems

Abstract: In this paper we present an efficient data compression scheme, the template run-length encoding (TRLE) scheme, for image composition of parallel volume rendering systems. Given an image with 2n/spl times/2n pixels, in the TRLE scheme, the image is treated as n/spl times/n blocks and each block has 2/spl times/2 pixels. Since a pixel can be a blank or non-blank pixel, there are 16 templates in a block. To compress an image, the TRLE scheme uses the templates to encode blocks row by row. Blocks in the same row are encoded as a TRLE-sequence. By packing all TRLE-sequences in a packet, the packet is the compressed partial image that can be sent/received among processors. To evaluate the performance of the TRLE scheme, we compare the proposed scheme with the BR, the RLE, and the BRLC schemes. Since a data compression scheme needs to cooperate with some data communication schemes, in the implementation, the binary-swap (BS), the parallel-pipelined (PP), and the rotate-tiling (RT) data communication schemes are used. By combining the four data compression schemes with the three data communication schemes, we have twelve image composition methods. These twelve methods are implemented on a PC cluster The data computation time and the data communication time are measured. The experimental results show that the TRLE data compression scheme with the RT data communication scheme outperforms other eleven image composition methods.