<title>Nonlinear interpolative decoding of standard transform coded images and video</title>

Abstract

We show that in a standard transform coding scheme of images or video, the decoder can be implemented by a table lookup technique without the explicit use of inverse transformation. In this new decoding method, each received code index of a transform coefficient addresses a particular codebook to fetch a component code vector that resembles the basis vector of the linear transformation. The output image is then reconstructed by summing a small number of non-zero component code vectors. With a set of well designed codebooks, this new decoder can exploit the correlation among the quantized transform coefficients to achieve better rate- distortion performance than the conventional decoding method. An iterative algorithm for designing a set of locally optimal codebooks from a training set of images is presented. We demonstrate that this new idea can be applied to decode improved quality pictures from the bit stream generated from a standard encoding scheme of still images or video, while the complexity is low enough to justify practical implementation.