Feature-Preserving Image Coding for Very Low Bit Rates

Many progressive wavelet-based image coders are designed for good performance on natural images. They attempt to achieve the greatest reduction in mean squared error (MSE) with each bit sent, an approach that is most effective when the image is composed chiefly of low-frequency content. Many images, however, include sharp-edged objects, text characters or graphics that are not well handled by standard wavelet-based methods. These features, which may contain information important for recognition, become distorted and obscured when highly compressed by standard wavelet-based methods. In this paper, we present a new progressive image coder that treats an image as being composed of three types of information: edges, texture, and edge-associated detail. The locations of important edges are encoded using line graphic techniques. Texture is encoded using a wavelet-based zerotree approach. Detail near edges – that cannot be efficiently encoded as texture – is encoded separately with a bitplane coding technique. With this approach, features in the image that may be important for recognition are well preserved, even at low bit rates.