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Comparative Study and Analysis of DWT-SPIHT with DWT-EZW Method for Image Compression

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dc.contributor.author Bhatt, Upendra Mohan
dc.date.accessioned 2025-01-20T09:13:38Z
dc.date.available 2025-01-20T09:13:38Z
dc.date.issued 2023-05
dc.identifier.uri https://ieeexplore.ieee.org/abstract/document/10125692
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16828
dc.description.abstract The use of digital photographs has increased along with the development of digital technologies. Due to the vast amounts of information it contains, digital photographs need a lot of storage space, as well as bigger transmission bandwidths and longer transmission times. Therefore, on compressing the images all the redundant bits of information present in the image under test are removed while keeping only the essential information needed to reconstruct the image later on. In this study, DWT-SPIHT technique is introduced, which may be used to compress and reconstruct images at various degrees of wavelet decomposition across wavelet families that were initially a subdivision of the MATLAB wavelet family. Simulations have been conducted on Cameraman Image during this work of different resolution at different levels of decomposition and for different types of thresholding techniques to prove that this algorithm works well and provide us with the good reconstruction quality of the image. The simulation results demonstrate that, when compared to the DWT-EZW algorithm, the proposed DWT-SPIHT algorithm performs significantly better in terms of evaluation parameters like peak signal to noise ratio (PSNR), mean square error (MSE), and visual perception at higher compression ratios (CR) and low bit per pixel values (BPP). en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject EEE en_US
dc.subject Discrete Wavelet Transform en_US
dc.subject Embedded Zero Tree Wavelet en_US
dc.subject Peak Signal to Noise ratio en_US
dc.subject Compression Ratio en_US
dc.subject Thresholding en_US
dc.title Comparative Study and Analysis of DWT-SPIHT with DWT-EZW Method for Image Compression en_US
dc.type Article en_US


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