A fast matrix quantizer for image encoding

This paper discusses a multi-stage matrix quantizer with a tree structure for image encoding wherein the number of searches required is a linear function of the product of the matrix size and the bit rate rather than an exponential one as in the case of a full search encoder. A two-step nine-way classification procedure is employed in order to preserve the edge contents of images. Further data rate reduction is achieved by preprocessing the images with a simple linear Hadamard transformer. A kl subblock of the input image is classified nine ways to detect the edge orientation. If it is not an edge a shade codebook is designed. Eight different codebooks are generated to accommodate each of the edge orientations under consideration. It is observed that the staircase degradation due to quantization is greatly reduced when edge detection is used. It is also found that the degradation due to tree encoding is only about 0.5 dB as compared to full search encoding.