The proposed Gray coding and XOR technique achieved a maximum compression ratio of 2.30 compared to 1.12 for PVRG-JPEG lossless compression on grayscale X-ray medical images.
Grayscale X-ray images collected from Kaggle.com
Multi-stage coding scheme combining Gray coding, adaptive Quadtree partitioning, logic minimization, and XOR-based residual processing
Logic Coding with Fixed Block Size, Logic Coding with Adaptive Segmentation, and PVRG-JPEG (Lossless)
Compression ratio
The proposed lossless medical image compression framework using logic minimization and XOR-based refinement improves compression ratios for X-ray images compared to standard methods.
Medical image compression is an active research area owing to the growth of the volume of medical image data in digital form. A method for lossless compression of medical images was proposed using logic minimization. The grayscale medical image is split into bit planes, and each bit plane is divided into blocks of fixed size, e.g., 8 × 4. The binary bit stream resulting from each of these blocks is treated as the output of a Boolean function, and logic minimization is attempted for a compact form. If this step fails to give a compact representation, the bits are stored as such. In this study, an extendable framework for lossless compression of medical images is presented. The bit plane is adaptively divided using a Quadtree to capture large uniform areas as leaf nodes. The non-uniform blocks at the leaf node are subjected to a logic minimization approach, as in the case of fixed-size blocks in previous related work. To improve the result further, the original image is gray-coded as a pre-processing step. On the bit plane, an XOR operation is done for the current block with the neighboring block for redundancy removal. This framework allows further exploration with the incorporation of other Boolean function representation techniques to enhance the compression.
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Swathi Pai M.
Jacob Augustine
Pamela Vinitha Eric
International Journal of Advanced Computer Science and Applications
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M. et al. (Thu,) conducted a other in Grayscale X-ray medical images for lossless compression. Multi-stage lossless medical image compression framework using Gray coding, adaptive Quadtree partitioning, logic minimization with ESPRESSO algorithm, and XOR-based residual processing vs. Logic coding with fixed block size, Adaptive segmentation only, and PVRG-JPEG lossless compression was evaluated on Compression ratio (size of original image / size of compressed image) for lossless compression of grayscale X-ray medical images (Compression ratio 2.30 vs 1.12). The proposed Gray coding and XOR technique achieved a maximum compression ratio of 2.30 compared to 1.12 for PVRG-JPEG lossless compression on grayscale X-ray medical images.
www.synapsesocial.com/papers/69abc1b45af8044f7a4eaa4f — DOI: https://doi.org/10.14569/ijacsa.2026.0170219