Nonlinear approximation based image recovery using adaptive sparse reconstructions and iterated denoising - Part II: Adaptive algorithms

IEEE Transactions on Image Processing

Volumn 15, Issue 3, 2006, Pages 555-571

  Guleryuz, Onur G ^a  

^a DOCOMO USA LABS   (United States)

Author keywords

Error concealment; Image recovery; Inpainting iterated denoising; Nonlinear approximation; Sparse recovery; Sparse representation

Indexed keywords

ADAPTIVE ALGORITHMS; APPROXIMATION THEORY; COMPUTER SIMULATION; ESTIMATION; MATHEMATICAL TRANSFORMATIONS;

ADAPTIVE SPARSE RECONSTRUCTION; ERROR CONCEALMENT; IMAGE RECOVERY; INPAINTING ITERATED DENOISING; NONLINEAR APPROXIMATION; SPARSE RECOVERY; SPARSE REPRESENTATION;

IMAGE PROCESSING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER GRAPHICS; COMPUTER SIMULATION; EVALUATION; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; METHODOLOGY; NONLINEAR SYSTEM; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER GRAPHICS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; INFORMATION STORAGE AND RETRIEVAL; MODELS, STATISTICAL; NONLINEAR DYNAMICS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 32944477217     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2005.863055     Document Type: Article

References (14)

1. M. Bertalmio, L. Vese, G. Sapiro, and S. Osher, "Simultaneous structure and texture image inpainting," IEEE Trans. Image Process., vol. 12, no. 8, pp. 882-889, Aug. 2003.
2. J. S. De Bonet, "Multiresolution sampling procedure for analysis and synthesis of texture images," presented at the ACM SIGGRAPH, Jul. 1997.
3. O. G. Guleryuz, Linear, worst-case estimators for denoising quantization noise in transform coded images, in IEEE Trans. Image Process., to be published.
4. O. G. Guleryuz, "On missing data prediction using sparse signal models: A comparison of atomic decompositions with iterated denoising," presented at the SPIE Conf. Wavelets XI, in Mathematical Methods, San Diego, CA, Aug. 2005.
5. O. G. Guleryuz, "Nonlinear approximation based image recovery using adaptive sparse reconstructions and iterated denoising - Part I: Theory," IEEE Trans. Image Process., vol. 15, no. 3, pp. 539-554, Mar. 2006.
6. O. G. Guleryuz, "Predicting wavelet coefficients over edges using estimates based on nonlinear approximants," presented at the Data Compression Conf., Apr. 2004.
7. O. G. Guleryuz, "Weighted overcomplete denoising," presented at the Asilomar Conf. Signals and Systems, Pacific Grove, CA, Nov. 2003.
8. N. G. Kingsbury "A dual-tree complex wavelet transform with improved orthogonality and symmetry properties," presented at the IEEE Conf. Image Processing, Vancouver, BC, Canada, Sep. 2000.
9. X. Li and M. T. Orchard, "Novel sequential error-concealment techniques using orientation adaptive interpolation," IEEE Trans. Circuits Syst. Video Technol., vol. 12, no. 10, pp. 857-864, Oct. 2002.
10. A. V. Oppenheim and R. W. Schafer, Discrete-Time Signal Processing. Upper Saddle River, NJ: Prentice-Hall, 1999.
11. J. Portilla and E. P. Simoncelli, "A parametric texture model based on joint statistics of complex wavelet coefficients," Int. J. Comput. Vis., vol. 40, no. 1, pp. 49-71, Oct. 2000.
12. J. K. Romberg, H. Choi, and R. G. Baraniuk, A hidden Markov tree model for the complex wavelet transform. preprint.
13. [Online]. Available: http://eeweb.poly.edu/~onur/source.html
14. [Online]. Available: http://www-white.media.mit.edu/vismod/imagery/ VisionTexture/vistex.html