A new integer image coding technique based on orthogonal polynomials

Authors:
R. Krishnamoorthi;N. Kannan
Affiliations:
Computer Vision Laboratory, Department of Information Technology, Bharathidasan Institute of Technology, Anna University, Trichy 620 024, Tamilnadu, India;Computer Vision Laboratory, Department of Information Technology, Bharathidasan Institute of Technology, Anna University, Trichy 620 024, Tamilnadu, India
Venue:
Image and Vision Computing
Year:
2009

Citing 23
Cited 4

A Theory for Multiresolution Signal Decomposition: The Wavelet Representation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Discrete cosine transform: algorithms, advantages, applications

Discrete cosine transform: algorithms, advantages, applications
The JPEG still picture compression standard

Communications of the ACM - Special issue on digital multimedia systems
Fast codebook generation algorithm for vector quantization of images

Pattern Recognition Letters
Wavelets and subband coding

Wavelets and subband coding
An orthogonal polynomials based framework for edge detection in 2-D monochrome images

Pattern Recognition Letters
Color edge extraction using orthogonal polynomials based zero crossings scheme

Information Sciences: an International Journal
Transform coding of monochrome images with a statistical design of experiments approach to separate noise

Pattern Recognition Letters
Discrete Cosine Transfom

IEEE Transactions on Computers
Embedded image coding using zerotrees of wavelet coefficients

IEEE Transactions on Signal Processing
Data compression and harmonic analysis

IEEE Transactions on Information Theory
The JPEG2000 still image coding system: an overview

IEEE Transactions on Consumer Electronics
Constrained-storage vector quantization with a universal codebook

IEEE Transactions on Image Processing
Line-based, reduced memory, wavelet image compression

IEEE Transactions on Image Processing
A fast exact GLA based on code vector activity detection

IEEE Transactions on Image Processing
Sparse geometric image representations with bandelets

IEEE Transactions on Image Processing
Image coding using wavelet transform

IEEE Transactions on Image Processing
Multiscale Hybrid Linear Models for Lossy Image Representation

IEEE Transactions on Image Processing
Improvement of DCT-Based Compression Algorithms Using Poisson's Equation

IEEE Transactions on Image Processing
Optimally adaptive transform coding

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
Low-Complexity Multiresolution Image Compression Using Wavelet Lower Trees

IEEE Transactions on Circuits and Systems for Video Technology
DCT-based codebook design for vector quantization of images

IEEE Transactions on Circuits and Systems for Video Technology

Fast and iterative algorithm for iris detection with orthogonal polynomials transform

Proceedings of the 2011 International Conference on Communication, Computing & Security
Minimum distortion clustering technique for orthogonal polynomials transform vector quantizer

Proceedings of the 2011 International Conference on Communication, Computing & Security
A multiresolution approach for rotation invariant texture image retrieval with orthogonal polynomials model

Journal of Visual Communication and Image Representation
Fast communication: Generalized adaptive Bayesian Relevance Feedback for image retrieval in the Orthogonal Polynomials Transform domain

Signal Processing

Quantified Score

Hi-index	0.01

Visualization

Abstract

In this paper, a new image coding scheme based on orthogonal polynomials has been presented. From a set of orthogonal polynomial functions, we first obtain the polynomial operators and polynomial basis operators of different width to propose the polynomial transform coding. After applying the proposed transformation, the transform coefficients are threshold coded using quantization and bit allocation as in JPEG baseline system. The performance of the proposed transform coding is reported by computing peak signal-to-noise ratio (PSNR). The proposed coding scheme is also compared with other transform coding schemes such as Discrete Cosine Transform and Discrete Wavelet Transforms.