Image transmission and compression techniques using SPIHT and EZW in WSN

Deepthi, S. Aruna; Rao, E. Sreenivasa; Prasad, M. N. Giri

doi:10.1109/icisc.2018.8398984

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…Most reduced memory SPIHT algorithms that exist in the literature adopt the linear indexing technique to map the DWT image into a 1D array of the same image size [12][13][14]. However, this technique demands either storing the DWT image into the main memory and then writing it into a 1D array or both DWT image and the 1D array must be available in the RAM at the same time [15].…”

Section: Introductionmentioning

confidence: 99%

Scalable image compression algorithms with small and fixed-size memory

Al-Janabi

Harbi

Hassan

2023

SIViP

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The SPIHT algorithm is characterized by low computational complexity, good performance, and the production of an embedded bitstream that can be decoded at several bit-rates with image quality enhancement as more bits are received. However, it suffers from the enormous computer memory consumption due to utilizing linked lists of size of about 2-3 times the image size to save the coordinates of the image pixels and the generated sets. In additions, it does not exploit the multiresolution feature of the wavelet transform to produce a resolution scalable bitstream by which the image can be decoded at numerous resolutions (sizes). The Single List SPIHT (SLS) algorithm resolved the high memory problem of SPIHT by using only one list of fixed size equals to just 1/4 the image size, and an average of 2.25 bits/pixel. This paper introduces two new algorithms that are based on SLS. The first algorithm modifies SLS to reduce its complexity and improve its performance. The second algorithm, which is the major contribution of the work, upgrades the modified SLS to produce a bitstream that is both quality and resolution scalable (highly scalable). As such, the algorithm is very suitable for the modern heterogeneous nature of the Internet users to satisfy their different capabilities and desires in terms of image quality and resolution.

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Section: Introductionmentioning

confidence: 99%

Scalable image compression algorithms with small and fixed-size memory

Al-Janabi

Harbi

Hassan

2023

SIViP

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Image Compression in Wireless Sensor Networks Using Autoencoder and RBM Method

Deepthi

Rao²,

Prasad

2019

Lecture Notes in Networks and Systems

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Scalable Image Compression Algorithms with Small and Fixed- Size Memory

Al-Janabi

Harbi

Hassan

2022

Preprint

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The SPIHT algorithm is characterized by low computational complexity, good performance, and the production of an embedded bitstream that can be decoded at several bit-rates with image quality enhancement as more bits are received. However, it suffers from the enormous computer memory consumption due to utilizing linked lists of size of about 2–3 times the image size to save the coordinates of the image pixels and the generated sets. In additions, it does not exploit the multi-resolution feature of the wavelet transform to produce a resolution scalable bitstream by which the image can be decoded at numerous resolutions (sizes). The Single List SPIHT (SLS) algorithm resolved the high memory problem of SPIHT by using only one list of fixed size equals to just 1/4 the image size, and an average of 2.25 bits/pixel. This paper introduces two new algorithms that are based on SLS. The first algorithm modifies SLS to reduce its complexity and improve its performance. The second algorithm, which is the major contribution of the work, upgrades the modified SLS to produce a bitstream that is both quality and resolution scalable (highly scalable). As such, the algorithm is very suitable for the modern heterogeneous nature of the Internet users to satisfy their different capabilities and desires in terms of image quality and resolution.

show abstract

Image transmission and compression techniques using SPIHT and EZW in WSN

Cited by 3 publications

References 2 publications

Scalable image compression algorithms with small and fixed-size memory

Scalable image compression algorithms with small and fixed-size memory

Image Compression in Wireless Sensor Networks Using Autoencoder and RBM Method

Scalable Image Compression Algorithms with Small and Fixed- Size Memory

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