Differential Huffman Coding Approach for Lossless Compression of Medical Images

2020 ◽  
pp. 579-589
Author(s):  
Arjan Singh ◽  
Baljit Singh Khehra ◽  
Gursheen Kaur Kohli
Keyword(s):  
Medical Images ◽  
Lossless Compression ◽  
Huffman Coding

scholarly journals Lossless Compression of Medical Images based on the Differential Probability of Images

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Medical Image ◽  
Large Scale ◽  
Medical Images ◽  
Lossless Compression ◽  
Differential Method ◽  
Huffman Coding ◽  
Difference Matrix ◽  
Differential Probability ◽  
Compression Effect ◽  
The Difference

Lossless compression is crucial in the remote transmission of large-scale medical image and the retainment of complete medical diagnostic information. The lossless compression method of medical image based on differential probability of image is proposed in this study. The medical image with DICOM format was decorrelated by the differential method, and the difference matrix was optimally coded by the Huffman coding method to obtain the optimal compression effect. Experimental results obtained using the new method were compared with those using Lempel–Ziv–Welch, modified run–length encoding, and block–bit allocation methods to verify its effectiveness. For 2-D medical images, the lossless compression effect of the proposed method is the best when the object region is more than 20% of the image. For 3-D medical images, the proposed method has the highest compression ratio among the control methods. The proposed method can be directly used for lossless compression of DICOM images.

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.

scholarly journals On the Randomness of Compressed Data

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 196
Author(s):  
Shmuel T. Klein ◽  
Dana Shapira
Keyword(s):  
Lossless Compression ◽  
Arithmetic Coding ◽  
Huffman Coding ◽  
Compression Method ◽  
Random Data ◽  
Present Evidence ◽  
Compressed Data ◽  
Good Compression

It seems reasonable to expect from a good compression method that its output should not be further compressible, because it should behave essentially like random data. We investigate this premise for a variety of known lossless compression techniques, and find that, surprisingly, there is much variability in the randomness, depending on the chosen method. Arithmetic coding seems to produce perfectly random output, whereas that of Huffman or Ziv-Lempel coding still contains many dependencies. In particular, the output of Huffman coding has already been proven to be random under certain conditions, and we present evidence here that arithmetic coding may produce an output that is identical to that of Huffman.

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