Abstract
In this paper, more efficient, low-complexity and reliable region of interest (ROI) image codec for compressing smooth low texture remote sensing images is proposed. We explore the efficiency of the modified ROI codec with respect to the selected set of convenient wavelet filters, which is a novel method. Such ROI coding experiment analysis representing low bit rate lossy to high quality lossless reconstruction with timing analysis is useful for improving remote sensing ground truth surveillance efficiency in terms of time and quality. The subjective [i.e. fair, five observer (HVS) evaluations using enhanced 3D picture view Hyper memory display technology] and the objective results revealed that for faster ground truth ROI coding applications, the Symlet-4 adaptation performs better than Biorthogonal 4.4 and Biorthogonal 6.8. However, the discrete Meyer wavelet adaptation is the best solution for delayed ROI image reconstructions.
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Project (No. 2004144013) supported by the Chinese Government Scholarship Council, China
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Kumarayapa, A., Zhang, Y. More efficient ground truth ROI image coding technique: implementation and wavelet based application analysis. J. Zhejiang Univ. - Sci. A 8, 835–840 (2007). https://doi.org/10.1631/jzus.2007.A0835
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DOI: https://doi.org/10.1631/jzus.2007.A0835
Key words
- Smooth low texture remote sensing (SLTRS) image
- Modified region of interest (ROI) image codec
- Wavelet filters
- Low bit rate (LBR)
- High bit rate (HBR)
- ROI coding