Compression of Hyperspectral Images by Using DWT and SPIHT

Veera Navendra Reddy*, 0**
* PG Scholar, Department of Electronics and Communication Engineering, JNTUACE, Pulivendula, Andra Pradesh, India.
** Associate Professor, Department of Electronics Communication Engineering, JNTUACE, Pulivendula, Andra Pradesh, India.
Periodicity:March - May'2017
DOI : https://doi.org/10.26634/jpr.4.1.13643

Abstract

The major aim of compression is to remove insignificance attached in redundancy of image-information in order to store or transmit information efficiently. Compression is a way of writing secret information using less fragments than an original picture would use. The Discrete-Wavelet-Transform (DWT) is comparatively recent compared to Discrete-Cosine Transform (DCT) with necessary properties. It achieves this with the redundancy problem of only for 2-dimensional signals that are considerably not up to the non-decimated DCT. A new compression technique supported DWT and Set Partitioning In Hierarchical Trees (SPIHT) has been discussed. Approximate shift is not varied, smart directional-property process influences the properties of DWT making it a better object for compression. A varied SPIHT process is introduced to expand its efficiency for compression. To increase security of the hosts and raise the effectiveness of the image, the DWT and SPIHT methods have been employed.

Keywords

Medical Image, DWT with SPIHT Encoding Process, Reconstruct Image, Data Extraction

How to Cite this Article?

Reddy, K. V. N., and Sivappagari, C. M. R. (2017). Compression of Hyperspectral Images by Using DWT and SPIHT. i-manager’s Journal on Pattern Recognition, 6(1), 40-62. https://doi.org/10.26634/jpr.4.1.13643

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