Block-based segmentation and adaptive coding for visually lossless compression of scanned documents

This paper presents a novel block-based segmentation and adaptive coding (BSAC) algorithm for visually lossless compression of scanned documents that contain not only photographic images but also text and graphic images. For such a compound image source, we structure the image into nonoverlapping blocks and classify each block into four different classes based on the empirical statistics within the block. Different coding strategies are applied to different classes in order to achieve the very best compression performance. Our new block-based image coder is able to provide visually lossless compression of scanned documents at the bit rate of around 1~1.5 bpp with modest computational complexity and very low memory requirement