Lossless compression of biomedical images using block-based arithmetic encoding employing resolution independent gradient edge detector

2022 ◽  
Vol 16 (1) ◽  
pp. 67
Author(s):  
Emjee Puthooran ◽  
Urvashi Sharma ◽  
Meenakshi Sood
Keyword(s):  
Lossless Compression ◽  
Edge Detector ◽  
Biomedical Images ◽  
Block Based

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.

An efficient block based lossless compression of medical images

Optik ◽  
2016 ◽  
Vol 127 (2) ◽  
pp. 754-758 ◽  
Author(s):  
D. Venugopal ◽  
S. Mohan ◽  
Sivanantha Raja
Keyword(s):  
Medical Images ◽  
Lossless Compression ◽  
Block Based

scholarly journals A Block-Based Arithmetic Entropy Encoding Scheme for Medical Images

2020 ◽  
Vol 15 (3) ◽  
pp. 65-81 ◽  
Author(s):  
Urvashi Sharma ◽  
Meenakshi Sood ◽  
Emjee Puthooran ◽  
Yugal Kumar
Keyword(s):  
Medical Images ◽  
Predictive Coding ◽  
Block Size ◽  
Lossless Compression ◽  
Threshold Values ◽  
Efficient Coding ◽  
Coding Efficiency ◽  
Block Based ◽  
Entropy Encoding ◽  
Efficiency Rate

The digitization of human body, especially for treatment of diseases can generate a large volume of data. This generated medical data has a large resolution and bit depth. In the field of medical diagnosis, lossless compression techniques are widely adopted for the efficient archiving and transmission of medical images. This article presents an efficient coding solution based on a predictive coding technique. The proposed technique consists of Resolution Independent Gradient Edge Predictor16 (RIGED16) and Block Based Arithmetic Encoding (BAAE). The objective of this technique is to find universal threshold values for prediction and provide an optimum block size for encoding. The validity of the proposed technique is tested on some real images as well as standard images. The simulation results of the proposed technique are compared with some well-known and existing compression techniques. It is revealed that proposed technique gives a higher coding efficiency rate compared to other techniques.

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