Depth-First Coding for Multivalued Pictures Using Bit-Plane Decomposition

A data compression technique using a bit-plane decomposition strategy of multivalued images is described. Although the bit-plane decomposition is mainly used for image transmission, our method takes the image expression for image database into consideration. It has two merits which are a hierarchical representation using depth-first (DF) expression and a simple noise reduction algorithm on the DF expression that is similar to human perception. DF expression is useful for image expansion, rotation, etc. We will study what information in an image should be eliminated as a noise reduction. Noise-like patterns in an image are uniformalized and the edge and smooth surfaces remain nearly unchanged. They are not blurred, but instead are a little enhanced. In this paper, we study a property of black-and-white (BAY) boundary points on bit-planes. The algorithm of the uniformalization process with a DF-expression of an image is described for coding. The experiment for real image data is carried out by a comparison to the other methods, and the results are discussed.