A vector quantizer for image restoration

An algorithm based on nonlinear interpolative vector quantization (NLIVQ) is presented which accomplishes image restoration concurrently with image compression. The algorithm is applied to the problem of deblurring noise-free diffraction-limited images by training with a large set of blurred and ori...

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Bibliographic Details
Published inProceedings of 3rd IEEE International Conference on Image Processing Vol. 3; pp. 439 - 441 vol.3
Main Authors Sheppard, D.G., Bilgin, A., Hunt, B.R., Marcellin, M.W., Nadar, M.S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1996
Subjects
Diffraction
Image restoration
Nonlinear optics
Optical distortion
Optical signal processing
PSNR
Signal processing algorithms
Signal resolution
USA Councils
Vector quantization
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Summary:An algorithm based on nonlinear interpolative vector quantization (NLIVQ) is presented which accomplishes image restoration concurrently with image compression. The algorithm is applied to the problem of deblurring noise-free diffraction-limited images by training with a large set of blurred and original image pairs. Simulation results demonstrate a quantitative improvement in images processed by the algorithm, as measured by image peak signal-to-noise ratio (PSNR), as well as a significant improvement in perceived image quality. A theoretical formulation of the algorithm is presented along with a discussion of implementation, training and simulation results.
ISBN:9780780332591
0780332598
DOI:10.1109/ICIP.1996.560525