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Development and Performance Evaluation of Efficient Low-Complexity SPIHT Image Coder

Rajeev Mishra


Wavelet transform is one of the advanced, effective and computationally fast methods for image data as well as video compression. The wavelet based image compression is particularly a nonreversible method that has been growing computationally more complicated as they getting more accurate and reliable. In this work we have developed an image compression technique based on main concepts related to partial ordering of the coefficients of image matrix elements by magnitude with transmission of its order by a subset partitioning approach that is replicated at the decoder thereafter the ordered bit plane transmission of
refined bits is performed and at last exploitation of the self-similarity of the image wavelet transform across different scales is applied. The partial ordering is obtained by the comparison of coefficient element magnitudes to a set of octavely decreasing thresholds. The bit pattern represents that an element is significant or insignificant for a particular selection of given threshold, depending on whether or not it is above of that threshold. This algorithm offers an excellent performance can be better understood. These concepts involves partial
ordering by magnitude with a partitioning and sorting method such that the ordered bit plane transmission and exploitation of self-similarity in between different scales of image wavelet coefficients. The proposed image compression method present a different implementation, based on set partitioning in hierarchical trees (SPIHT), which provides even better performance than already reported extension of the wavelet based compressions that surpassed the performance of the conventional methods like DCT and run length like
codlings. The image compression files results are calculated by original images for compression ratio and with reconstructed by the decompression methods for PSNR. The results are found either comparable to or surpass previous results obtained by other computationally complex methods. In addition of this the developed compression and decompression methods are very fast, and the performance can be made faster, with only small loss in performance, by reducing the bitrates values.

Cite this Article
Rajeev Mishra. Development and performance evaluation of efficient lowcomplexity SPIHT image coder. Journal of Advanced Database Management & Systems. 2015; 2(3): 5–10p.


SPIHT, NLS, DWT, data compression, image coder

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