Memory-efficient spatial prediction image compression scheme

Authors:
Anil V. Nandi;L. M. Patnaik;R. M. Banakar
Affiliations:
Computational Neurobiology Group, Supercomputer Education and Research Center, Microprocessor Applications Laboratory, Indian Institute of Science, Bangalore 560 012, Karnataka, India;Computational Neurobiology Group, Supercomputer Education and Research Center, Microprocessor Applications Laboratory, Indian Institute of Science, Bangalore 560 012, Karnataka, India;Computational Neurobiology Group, Supercomputer Education and Research Center, Microprocessor Applications Laboratory, Indian Institute of Science, Bangalore 560 012, Karnataka, India
Venue:
Image and Vision Computing
Year:
2007

Citing 7
Cited 0

Digital Image Processing

Digital Image Processing
JPEG Still Image Data Compression Standard

JPEG Still Image Data Compression Standard
SPIHT image compression without lists

ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
Embedded image coding using zerotrees of wavelet coefficients

IEEE Transactions on Signal Processing
High performance scalable image compression with EBCOT

IEEE Transactions on Image Processing
A new, fast, and efficient image codec based on set partitioning in hierarchical trees

IEEE Transactions on Circuits and Systems for Video Technology
An efficient spatial prediction-based image compression scheme

IEEE Transactions on Circuits and Systems for Video Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

In prediction phase, the hierarchical tree structure obtained from the test image is used to predict every central pixel of an image by its four neighboring pixels. The prediction scheme generates the predicted error image, to which the wavelet/sub-band coding algorithm can be applied to obtain efficient compression. In quantization phase, we used a modified SPIHT algorithm to achieve efficiency in memory requirements. The memory constraint plays a vital role in wireless and bandwidth-limited applications. A single reusable list is used instead of three continuously growing linked lists as in case of SPIHT. This method is error resilient. The performance is measured in terms of PSNR and memory requirements. The algorithm shows good compression performance and significant savings in memory.