On the bitmap compression for joint coding and data hiding of AMBTC compressed images

The compressed code of Absolute Moment Block Truncation Coding (AMBTC) consists of quantized values (QVs) and bitmaps. The QVs exhibit greater predictability, and the bitmaps themselves carry more randomness. While existing joint coding and data hiding based methods have focused on compressing the QVs, none of them have addressed the coding of bitmaps. Furthermore, evidence also reveals that the sub-divided bitmaps exhibit a highly uneven pattern distribution. Therefore, we propose an efficient method to compress the bitmaps by representing sub-divided bitmaps as decimal digits. This exploits the varying frequency of certain digits, allowing Huffman encoding for shorter codewords to represent frequently occurring digits. Moreover, we have observed that less frequent digits, which require longer codewords, tend to appear among blocks with smaller difference of QVs. As a solution, we employ an adaptive approach to directly record the original bitmap when the difference is below a specific threshold. Otherwise, we employ Huffman encoding to reduce the code length. The experimental results demonstrate the effectiveness of our approach in reducing the storage space required for Lena’s bitmaps by 7.36