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

Authors: Urvashi Sharma; Meenakshi Sood; Emjee Puthooran

Addresses: Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Waknaghat, H.P., India ' Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Waknaghat, H.P., India ' Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Waknaghat, H.P., India

Abstract: The radiological modalities such as CT scanners, MRI, X-ray, etc., produce a tremendous amount of data which needs to be stored in hospitals due to legal reasons. Compressing medical images will result in efficient storage and transmission of the data over a communication channel. Lossy compression techniques have high coding efficiency but they are not suitable for quality critical biomedical image compression. Lossless coding is essential in such case. In this paper, a new technique is presented for lossless coding using resolution independent gradient edge detector (RIGED) and block adaptive arithmetic coding (BAAE) for different modalities of volumetric medical images. RIGED is used for pixel prediction and coding redundancy is removed using BAAE. The proposed approach performs better as compared to the state-of-the-art compression algorithms in terms of bits-per-pixel (BPP). Experimentation results showed that the proposed technique outperforms CALIC and the JPEG-LS by 0.18% and 6.65%.

Keywords: predictive coding; compressed image; bits per pixel; BPP; block adaptive arithmetic encoding; BAAE; compression ratio; computer aided technology.

DOI: 10.1504/IJCAET.2022.119538

International Journal of Computer Aided Engineering and Technology, 2022 Vol.16 No.1, pp.67 - 82

Received: 13 Nov 2018
Accepted: 26 Mar 2019
Published online: 09 Dec 2021 *

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