Pointwise shape-adaptive DCT for high-quality deblocking of compressed color images

We present an high-quality image deblocking algorithm based on the shape-adaptive DCT (SA-DCT). The SA-DCT is a low-complexity transform which can be computed on a support of arbitrary shape. This transform has been adopted by the MPEG-4 standard and it is found implemented in modern video hardware. The use of this shape-adaptive transform for denoising and deblurring has been recently proposed, showing a remarkable performance. In this paper we discuss and analyze the use of this approach for the deblocking of block-DCT compressed images. Particular emphasis is given to the deblocking of highly-compressed color images. Extensive simulation experiments attest the advanced performance of the proposed filtering method. The visual quality of the estimates is high, with sharp detail preservation, clean edges. Blocking and ringing artifacts are suppressed while salient image features are preserved. The SA-DCT filtering used for the chrominance channels allows to faithfully reconstruct the missing structural information of the chrominances, thus correcting color-bleeding artifacts.

[1]  Thomas Sikora,et al.  Shape-adaptive DCT for generic coding of video , 1995, IEEE Trans. Circuits Syst. Video Technol..

[2]  Nikolas P. Galatsanos,et al.  Regularized reconstruction to reduce blocking artifacts of block discrete cosine transform compressed images , 1993, IEEE Trans. Circuits Syst. Video Technol..

[3]  D. Lun,et al.  Application of singularity detection for the deblocking of JPEG decoded images , 1998 .

[4]  Ewout Vansteenkiste,et al.  Evaluation of fuzzy image quality measures using a multidimensional scaling framwork , 2006 .

[5]  Vladimir Katkovnik,et al.  A new method for varying adaptive bandwidth selection , 1999, IEEE Trans. Signal Process..

[6]  Peter Kauff,et al.  Shape-adaptive DCT with block-based DC separation and ΔDC correction , 1998, IEEE Trans. Circuits Syst. Video Technol..

[7]  Hong Yan,et al.  An efficient wavelet-based deblocking algorithm for highly compressed images , 2001, IEEE Trans. Circuits Syst. Video Technol..

[8]  A. Foi,et al.  POINTWISE SHAPE-ADAPTIVE DCT DENOISINGWITH STRUCTURE PRESERVATION IN LUMINANCE-CHROMINANCE SPACE , 2006 .

[9]  Sang Uk Lee,et al.  On the POCS-based postprocessing technique to reduce the blocking artifacts in transform coded images , 1998, IEEE Trans. Circuits Syst. Video Technol..

[10]  Michael T. Orchard,et al.  A deblocking algorithm for JPEG compressed images using overcomplete wavelet representations , 1997, IEEE Trans. Circuits Syst. Video Technol..

[11]  Karen O. Egiazarian,et al.  Shape-adaptive DCT for denoising and image reconstruction , 2006, Electronic Imaging.

[12]  Tao Chen,et al.  Adaptive postfiltering of transform coefficients for the reduction of blocking artifacts , 2001, IEEE Trans. Circuits Syst. Video Technol..

[13]  S. Marsi,et al.  A Simple Algorithm For The Reduction Of Blocking Artifacts In Images And Its Implementation , 1998, International 1998 Conference on Consumer Electronics.

[14]  Jiun-In Guo,et al.  An Energy-Aware IP Core Design for the Variable-Length DCT/IDCT Targeting at MPEG4 Shape-Adaptive Transforms , 2005, IEEE Trans. Circuits Syst. Video Technol..

[15]  A. Goldenshluger On Spatial Adaptive Estimation of Nonparametric Regression , 2004 .

[16]  Hong Yan,et al.  Blocking artifacts suppression in block-coded images using overcomplete wavelet representation , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[17]  S. Aign,et al.  Overview of the MPEG-4 Standard and Error Resilience Investigations , 1998 .

[18]  Karen O. Egiazarian,et al.  POINTWISE SHAPE-ADAPTIVE DCT AS AN OVERCOMPLETE DENOISING TOOL , 2005 .

[19]  Avideh Zakhor Iterative procedures for reduction of blocking effects in transform image coding , 1992, IEEE Trans. Circuits Syst. Video Technol..

[20]  Noel E. O'Connor,et al.  FPGA-based conformance testing and system prototyping of an MPEG-4 SA-DCT hardware accelerator , 2005, Proceedings. 2005 IEEE International Conference on Field-Programmable Technology, 2005..

[21]  Noel E. O'Connor,et al.  Region and object segmentation algorithms in the Qimera segmentation platform , 2003 .

[22]  Jaakko Astola,et al.  Directional varying scale approximations for anisotropic signal processing , 2004, 2004 12th European Signal Processing Conference.

[23]  Amir Averbuch,et al.  Deblocking of block-transform compressed images using weighted sums of symmetrically aligned pixels , 2005, IEEE Transactions on Image Processing.

[24]  Thomas Sikora,et al.  Low complexity shape-adaptive DCT for coding of arbitrarily shaped image segments , 1995, Signal Process. Image Commun..

[25]  Nikolas P. Galatsanos,et al.  Projection-based spatially adaptive reconstruction of block transform compressed images , 1994, Other Conferences.