ISPIHT-Improved SPIHT: A Simplified and Efficient Subband Coding Scheme

Singh, Yumnam Kirani

doi:10.1109/iccta.2007.79

Cited by 8 publications

(5 citation statements)

References 7 publications

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“…Works of class (a) are given in [16][17][18][19][20][21][22], and the memory savings are due to reduction of list entries or cancellation of the lists. As these works assume the complete original picture to be kept in the memory, these works do not comply to our use-case of little RAM in the sensor node.…”

Section: Related Workmentioning

confidence: 99%

Evaluation of the wavelet image two-line coder: A low complexity scheme for image compression

Rein

Fitzek

Gühmann

et al. 2015

Signal Processing: Image Communication

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Section: Related Workmentioning

confidence: 99%

Evaluation of the wavelet image two-line coder: A low complexity scheme for image compression

Rein

Fitzek

Gühmann

et al. 2015

Signal Processing: Image Communication

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“…In the second step the wavelet coefficients of maximum entropy and de-correlated bands are quantized and encoded using Improved SPHIT algorithm. ISPIHT is the wavelet based image compression method which provides the highest image quality [10].…”

Section: Multi Resolution 2-d Wavelet Decompositionmentioning

confidence: 99%

Multispectral Image Compression for various band images with High Resolution Improved DWT SPIHT

Raju¹,

Sankar²,

Naidu

et al. 2016

IJSIP

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Satellite imageries which comprises of various multispectral spectral bands pertaining to spectral and spatial information of the images acquired by latest multispectral sensor technology are rapidly increasing day by day in the recent years for onboard satellite remote sensing applications. A lossy multispectral image compression is desired by the exploitation of the redundancies present in the spatial and spectral information while preserving the vital and crucial information of the image objects to a certain extent. In this paper a novel approach is proposed for lossy multispectral image compression which is an extension to the earlier existing algorithms. In this proposed method the multispectral images are first enhanced with interpolation based super resolution technique to estimate a hi-resolution (HR) image from a low-resolution (LR) input image. Secondly the decorrelated spectral bands transformed by discrete wavelet transform (DWT), which contain maximum entropy, are selected and these representative spectral bands are quantized and encoded using Improved SPIHT (ISPIHT) algorithm. The algorithm has been designed for the optimization of maximum coding efficiency and for high compression ratio of bits per pixel per band when compared with the well known compression techniques.

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“…We categorize the work into two classes, the first one reducing the requirements for storage of intermediate data, and the second one concerning the maintenance of the picture data itself. Examples of the first class are given in [16,15,1,12,8,13,9], where the list of insignificant pixels (LIP), the list of significant pixels (LSP), and the list of insignificant sets (LIS) are reduced or excluded. As these lists are essential in Spiht and can require several MBytes of RAM, the reported memory savings are given in respect to the lists.…”

Section: 1: Related Workmentioning

confidence: 99%

Wavelet Image Two-Line Coder for Wireless Sensor Node with Extremely Little RAM

Rein

Lehmann

Gühmann

2009

2009 Data Compression Conference

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This paper gives a novel wavelet image two-line (Wi2l) coder that is designed to fulfill the memory constraints of a typical wireless sensor node. The algorithm operates line-wisely on picture data stored on the sensor's flash memory card while it requires approximatively 1.5 kByte RAM to compress a monochrome picture with the size of 256x256 Bytes. The achieved data compression rates are the same as with the set partitioning in hierarchical trees (Spiht) algorithm. The coder works recursively on two lines of a wavelet subband while intermediate data of these lines is stored to backward encode the wavelet trees. Thus it does not need any list but three small buffers with a fixed dimension. The compression performance is evaluated by a PCimplementation in C, while time measurements are conducted on a typical wireless sensor node using a modified version of the PC-code.

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ISPIHT-Improved SPIHT: A Simplified and Efficient Subband Coding Scheme

Cited by 8 publications

References 7 publications

Evaluation of the wavelet image two-line coder: A low complexity scheme for image compression

Evaluation of the wavelet image two-line coder: A low complexity scheme for image compression

Multispectral Image Compression for various band images with High Resolution Improved DWT SPIHT

Wavelet Image Two-Line Coder for Wireless Sensor Node with Extremely Little RAM

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