An adaptive interval generation method for efficient distance coding of binary images

Abstract

We proposed an adaptive method for more efficient distance-coding of binary images. The proposed method partitions the image into blocks where the interval sequences of zeros or ones can be calculated, as opposed to the conventional method where intervals are calculated by following a fixed scan order. In the proposed method, one can adaptively choose either horizontal or vertical scan within a block, depending on criteria based on entropy values. The resulting intervals tend to have lower entropies than the conventional non-adaptive methods, thereby allowing for higher compression than distance coding using a lossless codec. Our simulations on various test images demonstrated that (i) the proposed method achieved significantly higher compression than the non-adaptive distance coding method; (ii) the proposed method can be used as an efficient preprocessor of a lossless coder, offering higher compression than directly coding on the original images.