Title :
Lapped nonlinear interpolative vector quantization and image super-resolution
Author :
Sheppard, David G. ; Panchapakesan, Kannan ; Bilgin, Ali ; Hunt, Bobby R. ; Marcellin, Michael W.
Author_Institution :
Dept. of Electr. & Comput. Eng., Arizona Univ., Tucson, AZ, USA
fDate :
2/1/2000 12:00:00 AM
Abstract :
This article presents an improved version of an algorithm designed to perform image restoration via nonlinear interpolative vector quantization (NLIVQ). The improvement results from using lapped blocks during the decoding process. The algorithm is trained on original and diffraction-limited image pairs. The discrete cosine transform is again used in the codebook design process to control complexity. Simulation results are presented which demonstrate improvements over the nonlapped algorithm in both observed image quality and peak signal-to-noise ratio. In addition, the nonlinearity of the algorithm is shown to produce super-resolution in the restored images
Keywords :
decoding; discrete cosine transforms; image coding; image resolution; image restoration; interpolation; transform coding; vector quantisation; NLIVQ; algorithm training; codebook design; complexity control; decoding; diffraction-limited image pairs; discrete cosine transform; image quality; image restoration; image super-resolution; lapped blocks; lapped nonlinear interpolative vector quantization; nonlapped algorithm; nonlinear algorithm; nonlinearity; peak signal-to-noise ratio; simulation results; Algorithm design and analysis; Decoding; Diffraction; Discrete cosine transforms; Image quality; Image restoration; PSNR; Process control; Process design; Vector quantization;
Journal_Title :
Image Processing, IEEE Transactions on
