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1 November 1989A Pyramidal Image Coder with Contour-Based Interpolative Vector Quantization
The Laplacian pyramid is a versatile data structure that represents an image as a sequence of spatially filtered and decimated versions of the original image. To obtain an expanded approximation from the processed decimated samples, linear interpolation is commonly used due to its computational simplicity; however, linear interpolation does not consider the gray-level change in the neighborhood of each interpolated pixel, and thus creates unpleasant staircase effects near edges and visually annoying blocking effects in shade regions. This paper proposes a new pyramidal image coding algorithm using contour-based interpolative vector quantization (VQ) to obtain a perceptually better interpolated image through the use of edge information at each level of the pyramid. The basic idea is to code the image using VQ on a level-by-level basis in the hierarchical structure. The decimation implies that the redundancy existing over large image areas can be efficiently exploited by VQ of a low dimension. In order to improve the quality of the reconstructed image, an adaptive corrector stage is added at the final stage of the pyramid to selectively encode the residual errors as needed. The locations for correction are hierarchically predicted using the previously encoded data at the higher levels. The above scheme is a very efficient combination of VQ and contour-based interpolation in the hierarchical pyramid structure, and is amenable to progressive image transmission. Experimental results show that good reconstructed images are obtained at 0.25 bits per pixel with a reasonable coding complexity.
Yo-Sung Ho andAllen Gersho
"A Pyramidal Image Coder with Contour-Based Interpolative Vector Quantization", Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); https://doi.org/10.1117/12.970084
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Yo-Sung Ho, Allen Gersho, "A Pyramidal Image Coder with Contour-Based Interpolative Vector Quantization," Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); https://doi.org/10.1117/12.970084