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- W3191728148 abstract "This paper presents a novel wavelet-based image coder with low memory and low complexity for achieving better compression efficiency. The presented encoder employs the Fractional Wavelet Filter (FrWF) to calculate DWT Coefficients, which are quantized and encoded using SPIHT algorithm. Compression of Hyperspectral data is a challenge as a third dimension is added into it. It has spectral and spatial correlations, exploiting both the correlations, compression can be achieved. FrWF and SPIHT gives good compression to these images, simulation results have been shown by plotting the graph between PSNR and Bit rate. Hyperspectral images are temporally decomposed using convolution and then spatially decomposed using FrWF to achieve 3D wavelet transform and then 2D SPIHT has been done on each frames to achieve the encoded bitstream. To reconstruct the original image inverse procedure has been done. The effect of increasing temporal decomposition has been shown by plotting graphs between PSNR and Bit rate. Also the effect of filter lengths by using Daubechies 9/7 and 5/3 filters in temporal directions has been shown." @default.
- W3191728148 created "2021-08-16" @default.
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- W3191728148 date "2019-04-10" @default.
- W3191728148 modified "2023-09-29" @default.
- W3191728148 title "Fractional Wavelet Filter Based Discrete Wavelet Transform and SPIHT for Hyperspectral Image Compression" @default.
- W3191728148 hasPublicationYear "2019" @default.
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