Performance Analysis of Lossless Compression Algorithms on Medical Images

2018 ◽  
pp. 177-186
Author(s):  
I Made Alan Priyatna ◽  
Media A. Ayu ◽  
Teddy Mantoro
Keyword(s):  
Performance Analysis ◽  
Medical Images ◽  
Lossless Compression ◽  
Compression Algorithms

Secure and Efficient Medical Image Transmission by New Tailored Visual Cryptography Scheme with LS Compressions

2015 ◽  
Vol 7 (1) ◽  
pp. 26-50 ◽  
Author(s):  
S. Manimurugan ◽  
C. Narmatha
Keyword(s):  
Medical Image ◽  
Medical Images ◽  
Visual Cryptography ◽  
Lossless Compression ◽  
Image Transmission ◽  
Vital Role ◽  
Compression Algorithms ◽  
Merging Process ◽  
Visual Cryptography Scheme ◽  
Short Algorithm

Exchanging a medical image via network from one place to another place or storing a medical image in a particular place in a secure manner has become a challenge. To overwhelm this, secure medical image Lossless Compression (LC) schemes have been proposed. The original input grayscale medical images are encrypted by Tailored Visual Cryptography Encryption Process (TVCE) which is a proposed encryption system. To generate these encrypted images, four types of processes are adopted which play a vital role. These processes are Splitting Process, Converting Process, Pixel Process and Merging process. The encrypted medical image is compressed by proposed compression algorithms, i.e Pixel Block Short algorithm (PBSA) and one conventional Lossless Compression (LC) algorithm has been adopted (JPEG 2000LS). The above two compression methods are used to separate compression for encrypted medical images. And also, decompressions have been done in a separate manner. The encrypted output image which is generated from decompression of the proposed compression algorithm, JPEG 2000LS are decrypted by the Tailored Visual Cryptography Decryption Process (TVCD). To decrypt the encrypted grayscale medical images, four types of processes are involved. These processes are Segregation Process, Inverse Pixel Process, 8-Bit into Decimal Conversion Process and Amalgamate Process. However, this paper is focused on the proposed visual cryptography only. From these processes, two original images have been reconstructed which are given by two compression algorithms. Ultimately, two combinations are compared with each other based on the various parameters. These techniques can be implemented in the field for storing and transmitting medical images in a secure manner. The Confidentiality, Integrity and Availability (CIA property) of a medical image have also been proved by the experimental results. In this paper we have focused on only proposed visual cryptography scheme.

scholarly journals Using Predictive and Differential Methods with K2-Raster Compact Data Structure for Hyperspectral Image Lossless Compression

2019 ◽  
Vol 11 (21) ◽  
pp. 2461 ◽  
Author(s):  
Kevin Chow ◽  
Dion Tzamarias ◽  
Ian Blanes ◽  
Joan Serra-Sagristà
Keyword(s):  
Data Structure ◽  
Hyperspectral Image ◽  
Lossless Compression ◽  
Hyperspectral Images ◽  
Direct Access ◽  
Bit Rate ◽  
Compression Algorithms ◽  
Real Time Processing ◽  
Time Processing ◽  
Differential Encoding

This paper proposes a lossless coder for real-time processing and compression of hyperspectral images. After applying either a predictor or a differential encoder to reduce the bit rate of an image by exploiting the close similarity in pixels between neighboring bands, it uses a compact data structure called k 2 -raster to further reduce the bit rate. The advantage of using such a data structure is its compactness, with a size that is comparable to that produced by some classical compression algorithms and yet still providing direct access to its content for query without any need for full decompression. Experiments show that using k 2 -raster alone already achieves much lower rates (up to 55% reduction), and with preprocessing, the rates are further reduced up to 64%. Finally, we provide experimental results that show that the predictor is able to produce higher rates reduction than differential encoding.

scholarly journals Lossless Compression of Medical Image Sequences Using a Resolution Independent Predictor and Block Adaptive Encoding

2019 ◽  
Vol 9 (2) ◽  
pp. 69-79 ◽  
Author(s):  
Urvashi Sharma ◽  
Meenakshi Sood ◽  
Emjee Puthooran
Keyword(s):  
Medical Images ◽  
Block Size ◽  
Lossless Compression ◽  
Experimental Tests ◽  
Threshold Value ◽  
Image Resolution ◽  
Coding Efficiency ◽  
Volumetric Medical Images ◽  
Adaptive Encoding ◽  
Block Based

The proposed block-based lossless coding technique presented in this paper targets at compression of volumetric medical images of 8-bit and 16-bit depth. The novelty of the proposed technique lies in its ability of threshold selection for prediction and optimal block size for encoding. A resolution independent gradient edge detector is used along with the block adaptive arithmetic encoding algorithm with extensive experimental tests to find a universal threshold value and optimal block size independent of image resolution and modality. Performance of the proposed technique is demonstrated and compared with benchmark lossless compression algorithms. BPP values obtained from the proposed algorithm show that it is capable of effective reduction of inter-pixel and coding redundancy. In terms of coding efficiency, the proposed technique for volumetric medical images outperforms CALIC and JPEG-LS by 0.70 % and 4.62 %, respectively.

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