Pointwise Shape-Adaptive DCT for High-Quality Denoising and Deblocking of Grayscale and Color Images

The shape-adaptive discrete cosine transform (SA-DCT) transform can be computed on a support of arbitrary shape, but retains a computational complexity comparable to that of the usual separable block-DCT (B-DCT). Despite the near-optimal decorrelation and energy compaction properties, application of...

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Bibliographic Details
Published in:IEEE transactions on image processing Vol. 16; no. 5; pp. 1395 - 1411
Main Authors: Foi, A., Katkovnik, V., Egiazarian, K.
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.05.2007
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Anisotropic
Applied sciences
Artificial Intelligence
Blocking
Coding, codes
Color
Colorimetry - methods
Computation
Computational complexity
Computer Graphics
Confidence intervals
deblocking
Decorrelation
denoising
deringing
Detection, estimation, filtering, equalization, prediction
discrete cosine transform (DCT)
Discrete cosine transforms
Discrete transforms
Estimates
Exact sciences and technology
Filtering
Filtration
Fourier Analysis
Gray-scale
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image processing
Image reconstruction
Information Storage and Retrieval - methods
Information, signal and communications theory
Miscellaneous
Noise reduction
Numerical Analysis, Computer-Assisted
Shape
shape adaptive
Signal and communications theory
Signal processing
Signal Processing, Computer-Assisted
Signal, noise
Studies
Telecommunications and information theory
Transforms
Video coding
State of the art
Grey level image
Image processing
Noise reduction
Polynomial approximation
Data compression
Anisotropic
Artefact
discrete cosine transform (DCT)
Video signal processing
denoising
Image coding
deringing
Arbitrary shape body
Decorrelation
Discrete cosine transforms
Filtering
deblocking
Image compression
Computational complexity
Color image
Confidence interval
Luminance
Simulation
Signal processing
shape adaptive
Image denoising
ISSN:1057-7149, 1941-0042
Online Access:Get full text
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Summary:The shape-adaptive discrete cosine transform (SA-DCT) transform can be computed on a support of arbitrary shape, but retains a computational complexity comparable to that of the usual separable block-DCT (B-DCT). Despite the near-optimal decorrelation and energy compaction properties, application of the SA-DCT has been rather limited, targeted nearly exclusively to video compression. In this paper, we present a novel approach to image filtering based on the SA-DCT. We use the SA-DCT in conjunction with the Anisotropic Local Polynomial Approximation-Intersection of Confidence Intervals technique, which defines the shape of the transform's support in a pointwise adaptive manner. The thresholded or attenuated SA-DCT coefficients are used to reconstruct a local estimate of the signal within the adaptive-shape support. Since supports corresponding to different points are in general overlapping, the local estimates are averaged together using adaptive weights that depend on the region's statistics. This approach can be used for various image-processing tasks. In this paper, we consider, in particular, image denoising and image deblocking and deringing from block-DCT compression. A special structural constraint in luminance-chrominance space is also proposed to enable an accurate filtering of color images. Simulation experiments show a state-of-the-art quality of the final estimate, both in terms of objective criteria and visual appearance. Thanks to the adaptive support, reconstructed edges are clean, and no unpleasant ringing artifacts are introduced by the fitted transform
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ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2007.891788