Variable-length Run-Length Limited codes

2009 ◽  
Author(s):  
Luminita Scripcariu ◽  
Mircea-Daniel Frunza
Keyword(s):  
Variable Length ◽  
Run Length

scholarly journals A Novel Decode-Aware Compression Technique for Improved Compression and Decompression

2016 ◽  
pp. 120-125
Author(s):  
J. Suresh Babu ◽  
K. Tirumala Rao ◽  
P. Srinivas
Keyword(s):  
Compression Ratio ◽  
Variable Length ◽  
Compression Technique ◽  
Run Length ◽  
Access Delay ◽  
Variable Length Coding ◽  
Stream Size ◽  
Configuration Information ◽  
Good Compression ◽  
Bit Stream

With compressed bit streams, more configuration information can be stored using the same memory. The access delay is also reduced, because less bits need to be transferred through the memory interface. To measure the efficiency of bit stream compression, compression ratio (CR) is widely used as a metric. it is a major challenge to develop an efficient compression technique that can significantly reduce the bit stream size without sacrificing the decompression performance. Our approach combines the advantages of previous compression techniques with good compression ratio and those with fast decompression. This paper makes three important contributions. First, it performs smart placement of compressed bit streams to enable fast decompression of variable-length coding. Next, it selects bitmask-based compression parameters suitable for bit stream compression. Finally, it efficiently combines run length encoding and bitmask-based compression to obtain better compression and faster decompression.

scholarly journals Run Length Encoding Based Lossless MRI Image Compression Using LZW and Adaptive Variable Length Coding

2019 ◽  
Vol 54 (4) ◽  
Author(s):  
Nassir H. Salman ◽  
Enas Kh. Hassan
Keyword(s):  
Medical Imaging ◽  
Image Compression ◽  
Image Data ◽  
Variable Length ◽  
Imaging Data ◽  
Compression Technique ◽  
Run Length ◽  
Lossless Image Compression ◽  
Variable Length Coding ◽  
Mri Image

Medical image compression is considered one of the most important research fields nowadays in biomedical applications. The majority of medical images must be compressed without loss because each pixel information is of great value. With the widespread use of applications concerning medical imaging in the health-care context and the increased significance in telemedicine technologies, it has become crucial to minimize both the storage and bandwidth requirements needed for archiving and transmission of medical imaging data, rather by employing means of lossless image compression algorithms. Furthermore, providing high resolution and image quality preservation of the processed image data has become of great benefit. The proposed system introduces a lossless image compression technique based on Run Length Encoding (RLE) that encodes the original magnetic resonance imaging (MRI) image into actual values and their numbers of occurrence. The actual image data values are separated from their runs and they are stored in a vector array. Lempel–Ziv–Welch (LZW) is used to provide further compression that is applied to values array only. Finally the Variable Length Coding (VLC) will be applied to code the values and runs arrays for the precise amount of bits adaptively into a binary file. These bit streams are reconstructed using inverse LZW of the values array and inverse RLE to reconstruct the input image. The obtained compression gain is enhanced by 25% after applying LZW to the values array.

Characterization of Pancreas at Diabetic Patients in CT images using Texture Analysis

2017 ◽  
Vol 7 (7) ◽  
pp. 8
Author(s):  
Mona E. Elbashier ◽  
Suhaib Alameen ◽  
Caroline Edward Ayad ◽  
Mohamed E. M. Gar-Elnabi
Keyword(s):  
Size Distribution ◽  
Texture Analysis ◽  
Classification Accuracy ◽  
Ct Images ◽  
Diabetic Patients ◽  
Gray Level ◽  
Grey Level ◽  
Run Length ◽  
Interactive Data

This study concern to characterize the pancreas areato head, body and tail using Gray Level Run Length Matrix (GLRLM) and extract classification features from CT images. The GLRLM techniques included eleven’s features. To find the gray level distribution in CT images it complements the GLRLM features extracted from CT images with runs of gray level in pixels and estimate the size distribution of thesubpatterns. analyzing the image with Interactive Data Language IDL software to measure the grey level distribution of images. The results show that the Gray Level Run Length Matrix and  features give classification accuracy of pancreashead 89.2%, body 93.6 and the tail classification accuracy 93.5%. The overall classification accuracy of pancreas area 92.0%.These relationships are stored in a Texture Dictionary that can be later used to automatically annotate new CT images with the appropriate pancreas area names.

Performance enhancement of Echo Cancellation Using a Combination of Partial Update ( PU) Methods and New Variable Length LMS (NVLLMS) Algorithm

2018 ◽  
Vol 24 (5) ◽  
pp. 66
Author(s):  
Thamer M. Jamel ◽  
Faez Fawzi Hammood
Keyword(s):  
Mean Square Error ◽  
Return Loss ◽  
Performance Enhancement ◽  
Variable Length ◽  
Echo Cancellation ◽  
Convergence Time ◽  
Length Variation ◽  
Mean Square ◽  
Step Size ◽  
Echo Return Loss Enhancement

In this paper, several combination algorithms between Partial Update LMS (PU LMS) methods and previously proposed algorithm (New Variable Length LMS (NVLLMS)) have been developed. Then, the new sets of proposed algorithms were applied to an Acoustic Echo Cancellation system (AEC) in order to decrease the filter coefficients, decrease the convergence time, and enhance its performance in terms of Mean Square Error (MSE) and Echo Return Loss Enhancement (ERLE). These proposed algorithms will use the Echo Return Loss Enhancement (ERLE) to control the operation of filter's coefficient length variation. In addition, the time-varying step size is used.The total number of coefficients required was reduced by about 18% , 10% , 6%, and 16% using Periodic, Sequential, Stochastic, and M-max PU NVLLMS algorithms respectively, compared to that used by a full update method which  is very important, especially in the application of mobile communication since the power consumption must be considered. In addition, the average ERLE and average Mean Square Error (MSE) for M-max PU NVLLMS are better than other proposed algorithms.  

A Test Data Compression Scheme Based on Mixed Fixed and Variable Length Coding

2009 ◽  
Vol 31 (10) ◽  
pp. 1826-1834 ◽  
Author(s):  
Wen-Fa ZHAN ◽  
Hua-Guo LIANG ◽  
Feng SHI ◽  
Zheng-Feng HUANG
Keyword(s):  
Data Compression ◽  
Test Data ◽  
Variable Length ◽  
Test Data Compression ◽  
Compression Scheme ◽  
Variable Length Coding
Sign in / Sign up

Export Citation Format

Share Document