Scanned document compression using block-based hybrid video codec.

This paper proposes a hybrid pattern matching/transform-based compression method for scanned documents. The idea is to use regular video interframe prediction as a pattern matching algorithm that can be applied to document coding. We show that this interpretation may generate residual data that can be efficiently compressed by a transform-based encoder. The efficiency of this approach is demonstrated using H.264/advanced video coding (AVC) as a high-quality single and multipage document compressor. The proposed method, called advanced document coding (ADC), uses segments of the originally independent scanned pages of a document to create a video sequence, which is then encoded through regular H.264/AVC. The encoding performance is unrivaled. Results show that ADC outperforms AVC-I (H.264/AVC operating in pure intramode) and JPEG2000 by up to 2.7 and 6.2 dB, respectively. Superior subjective quality is also achieved.

Two-dimensional compression of surface electromyographic signals using column-correlation sorting and image encoders.

We present a new preprocessing technique for two-dimensional compression of surface electromyographic (S-EMG) signals, based on correlation sorting. We show that the JPEG2000 coding system (originally designed for compression of still images) and the H.264/AVC encoder (video compression algorithm operating in intraframe mode) can be used for compression of S-EMG signals. We compare the performance of these two off-the-shelf image compression algorithms for S-EMG compression, with and without the proposed preprocessing step. Compression of both isotonic and isometric contraction S-EMG signals is evaluated. The proposed methods were compared with other S-EMG compression algorithms from the literature.

Segmentation-driven compound document coding based on H.264/AVC-INTRA.

In this paper, we explore H.264/AVC operating in intraframe mode to compress a mixed image, i.e., composed of text, graphics, and pictures. Even though mixed contents (compound) documents usually require the use of multiple compressors, we apply a single compressor for both text and pictures. For that, distortion is taken into account differently between text and picture regions. Our approach is to use a segmentation-driven adaptation strategy to change the H.264/AVC quantization parameter on a macroblock by macroblock basis, i.e., we deviate bits from pictorial regions to text in order to keep text edges sharp. We show results of a segmentation driven quantizer adaptation method applied to compress documents. Our reconstructed images have better text sharpness compared to straight unadapted coding, at negligible visual losses on pictorial regions. Our results also highlight the fact that H.264/AVC-INTRA outperforms coders such as JPEG-2000 as a single coder for compound images.