Conditional Run-Length and Variable-Length Coding of Digital Pictures

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.

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

Journal of Southwest Jiaotong University ◽

10.35741/issn.0258-2724.54.4.23 ◽

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.

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