Abstract
Due to the rapid growth in the data acquired by the acquisition devices throws a challenge to propose efficient compression algorithm. Compression of digital images aims to transform the image into more compact form which is convenient for storage, transmission, processing and retrieval. This paper presents an effective and low computation complexity based image compression approach with Hierarchical coding using Hilbert transform. The presented Hilbert transform based scanning with Hierarchical coding is compared against state of art image coders and the experimental results with standard dataset images shows that the method yields higher metrical values than earlier methods. It can be concluded from the average of the results that PSNR is increased by 0.6 dB on average with respect to JPEG 2000 and ~ 2 dB with respect to SPIHT method. In a similar manner, the MSE and RMSE values are very low (0.78 units). The SSIM and correlation coefficient are utmost higher (0.99 units). These depict the high quality of the reconstructed compressed image.
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Krishna, V., Murali Mohan, K.V., Banala, R. et al. An effective hierarchical image coding approach with Hilbert scanning. Int J Syst Assur Eng Manag (2023). https://doi.org/10.1007/s13198-023-02060-6
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DOI: https://doi.org/10.1007/s13198-023-02060-6