Jacquin, A E
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

The author proposes an independent and novel approach to image coding, based on a fractal theory of iterated transformations. The main characteristics of this approach are that (i) it relies on the assumption that image redundancy can be efficiently exploited through self-transformability on a block-wise basis, and (ii) it approximates an original ...

Nanda, S Pearlman, W A
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

The authors consider the encoding of image subbands with a tree code that is asymptotically optimal for Gaussian sources and the mean squared error (MSE) distortion measure. They first prove that optimal encoding of ideally filtered subbands of a Gaussian image source achieves the rate distortion bound for the MSE distortion measure. The optimal ra...

Vlontzos, J A Kung, S Y
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

A hierarchical system for character recognition with hidden Markov model knowledge sources which solve both the context sensitivity problem and the character instantiation problem is presented. The system achieves 97-99% accuracy using a two-level architecture and has been implemented using a systolic array, thus permitting real-time (1 ms per char...

Guan, L Ward, R K
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

The maximum a posteriori (MAP) estimation technique is applied to the problem of restoring images distorted by noisy point spread functions and additive noise. The resulting MAP estimator is nonlinear and is obtained by numerically maximizing a conditional probability density function. The energy nonnegativity constraint is incorporated in the opti...

Norton, S J
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

The problem of reconstructing a vector field v(r) from its line integrals (through some domain D) is generally undetermined since v(r) is defined by two component functions. When v(r) is decomposed into its irrotational and solenoidal components, it is shown that the solenoidal part is uniquely determined by the line integrals of v(r). This is demo...

Chan, C K Po, L M
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

A technique for reducing the complexity of spatial-domain image vector quantization (VQ) is proposed. The conventional spatial domain distortion measure is replaced by a transform domain subspace distortion measure. Due to the energy compaction properties of image transforms, the dimensionality of the subspace distortion measure can be reduced dras...

Senoo, T Girod, B
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

Vector quantization for entropy coding of image subbands is investigated. Rate distortion curves are computed with mean square error as a distortion criterion. The authors show that full-search entropy-constrained vector quantization of image subbands results in the best performance, but is computationally expensive. Lattice quantizers yield a codi...

Desai, M D Jenkins, W K
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

Convolution backprojection (CBP) image reconstruction has been proposed as a means of producing high-resolution synthetic-aperture radar (SAR) images by processing data directly in the polar recording format which is the conventional recording format for spotlight mode SAR. The CBP algorithm filters each projection as it is recorded and then backpr...

Lawton, W M
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

Continuous versions of the multidimensional chirp algorithms compute the function G(y)=F(My), where F(y) is the Fourier transform of a function f(x) of a vector variable x and M is an invertible matrix. Discrete versions of the algorithms compute values of F over the lattice L(2)=ML(1 ) from values of f over a lattice L(1), where L(2) need not cont...

Das, M Loh, N K
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

The authors introduce two new one-dimensional multiplicative autoregressive (MAR) models for adaptive predictive coding of digitized images. The proposed scheme offers a number of advantages. These include easy implementability, a high signal-to-noise ratio at a moderate bit rate, and guaranteed stability of the predictive coder. Results of extensi...