Projection-based spatially adaptive reconstruction of block-transform compressed images.

Projection-based spatially adaptive reconstruction of block-transform compressed images. Research Abstract Details 

Research Abstract Table of Contents

Jump to the:

Projection-based spatially adaptive reconstruction of block-transform compressed images. Abstract Text:

Y Yang,N P Galatsanos,A K Katsaggelos,

At the present time, block-transform coding is probably the most popular approach for image compression. For this approach, the compressed images are decoded using only the transmitted transform data. We formulate image decoding as an image recovery problem. According to this approach, the decoded image is reconstructed using not only the transmitted data but, in addition, the prior knowledge that images before compression do not display between-block discontinuities. A spatially adaptive image recovery algorithm is proposed based on the theory of projections onto convex sets. Apart from the data constraint set, this algorithm uses another new constraint set that enforces between-block smoothness. The novelty of this set is that it captures both the local statistical properties of the image and the human perceptual characteristics. A simplified spatially adaptive recovery algorithm is also proposed, and the analysis of its computational complexity is presented. Numerical experiments are shown that demonstrate that the proposed algorithms work better than both the JPEG deblocking recommendation and our previous projection-based image decoding approach.

Projection-based spatially adaptive reconstruction of block-transform compressed images. Publishing Authors By Initials

Y Yang,NP Galatsanos,AK Katsaggelos,

For similar abstracts research abstracts see: abstracts research

PUBMED ID PMID:

MEDLINE DATE:

Projection-based spatially adaptive reconstruction of block-transform compressed images. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: IEEE transactions on image processing : a publicat

VOLUME: 4

Page Numbers: 896-908

Journal Abbreviation:

ISSN: 1057-7149

DAY: 21

MONTH: 02

YEAR: 1995

Projection-based spatially adaptive reconstruction of block-transform compressed images. Information

Number of References:

LANGUAGE: eng

NlmUniqueID: 9886191

Projection-based spatially adaptive reconstruction of block-transform compressed images. Keywords Mesh Terms:

KEYWORDS:

MESH TERMS:

Chemical & Substance for Abstract: Projection-based spatially adaptive reconstruction of block-transform compressed images. Information

Substance Name:

Registry Number:

Grant and Affiliation Information for Projection-based spatially adaptive reconstruction of block-transform compressed images.

AFFILIATION: Dept. of Electr. and Comput. Eng., Illinois Inst. of Technol., Chicago, IL.

Country: United States

AGENCY:

GRANT:

ACRONYM:

MEDLINETA: IEEE Trans Image Process

REFSOURCE:

DATABASENAME:

ACCESSION NUMBER:

Number Hits: 0

Projection-based spatially adaptive reconstruction of block-transform compressed images Related Publications

• A VQ-based blind image restoration algorithm.
• A recursive nonstationary MAP displacement vector field estimation algorithm.
• A video compression scheme with optimal bit allocation among segmentation, motion, and residual error.
• An HMM-based speech-to-video synthesizer.
• An adaptive regularized recursive displacement estimation algorithm.
• An operational rate-distortion optimal single-pass SNR scalable video coder.
• An optimal polygonal boundary encoding scheme in the rate distortion sense.
• An optimal quadtree-based motion estimation and motion-compensated interpolation scheme for video compression.
• General choice of the regularization functional in regularized image restoration.
• Hierarchical Bayesian image restoration from partially known blurs.
• Hybrid image segmentation using watersheds and fast region merging.
• Image restoration using a modified Hopfield network.
• Iterative maximum likelihood displacement field estimation in quantum-limited image sequences.
• Joint source-channel coding for motion-compensated DCT-based SNR scalable video.
• Low bit rate video coding using robust motion vector regeneration in the decoder.
• Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relation.
• Motion estimation of skeletonized angiographic images using elastic registration.
• Multichannel restoration of single channel images using a wavelet-based subband decomposition.
• Parameter Estimation in TV Image Restoration Using Variational Distribution Approximation.
• Parameter estimation in Bayesian high-resolution image reconstruction with multisensors.
• Projection-based spatially adaptive reconstruction of block-transform compressed images.
• Regularized constrained total least squares image restoration.
• Resolution enhancement of monochrome and color video using motion compensation.
• Simultaneous multichannel image restoration and estimation of the regularization parameters.
• Simultaneous recursive displacement estimation and restoration of noisy-blurred image sequences.
• Spatially adaptive wavelet-based multiscale image restoration.