In the domain of digital video coding, new technologies and solutions are emerging in a fast pace, targeting the needs of the evolving multimedia landscape. One of the questions that arises is how to assess these different video coding technologies in terms of compression efficiency. In this paper, several compression schemes are compared by means of peak signal-to-noise ratio (PSNR) and just noticeable difference (JND). The codecs examined are XviD 0.9.1 (conform to the MPEG-4 Visual Simple Profile), DivX 5.1 (implementing the MPEG-4 Visual Advanced Simple Profile), Windows Media Video 9, MC-EZBC and H.264/AVC AHM 2.0 (version JM 6.1 of the reference software, extended with rate control). The latter plays a key role in this comparison because the H.264/AVC standard can be considered as the de facto benchmark in the field of digital video coding. The obtained results show that H.264/AVC AHM 2.0 outperforms current proprietary and standards-based implementations in almost all cases. Another observation is that the choice of a particular quality metric can influence general statements about the relation between the different codecs.

In the digital prepress workflow, images are represented in the CMYK colour space. Lossy image compression alleviates the need for high storage and bandwidth capacities, resulting from the high spatial and tonal resolution. After the image has been printed on paper, the introduced visual quality loss should not be noticeable to a human observer. Since visual image quality depends on the compression algorithm both quantitatively and qualitatively, and since no visual image quality models incorporating the end‐to‐end image reproduction process are satisfactory, an experimental comparison is the only viable way to quantify subjective image quality. This paper presents the results from an intensive psychovisual study based on a two‐alternative forced‐choice approach involving 164 people, with expert and non‐expert observers distinguished. The primary goal is to evaluate two previously published adaptations of JPEG to CMYK images, and to determine a visually lossless compression ratio threshold for typical printing applications. The improvements are based on tonal decorrelation and overlapping block transforms. Results on three typical prepress test images indicate that the proposed adaptations are useful and that for the investigated printing configuration, compression ratios up to 20 can be used safely.

CMYK color images are used extensively in prepress applications. When compressing those color images one has to deal with four different color channels. Usually compression algorithms only take into account the spatial redundancy that is present in the image data. This approach does not yield an optimal data reduction since there also exists a high correlation between the different colors in natural images. This paper shows that a significant gain in data reduction can be achieved by exploiting this color redundancy. Some popular transform coders, including DCT‐based JPEG and the SPIHT wavelet coder, were used for reducing the spatial redundancy. The performance of the algorithms was evaluated using a quality criterion based on human perception like the mean CIEL*a*b*ΔE error.

This paper shows that an n x 1 integer vector can be exactly recovered from its Hadamard transform coefficients, even when 0.5 n log(2)(n) of the (less significant) bits of these coefficients are removed. The paper introduces a fast "lossless" dequantization algorithm for this purpose. To investigate the usefulness of the procedure in data compression, the paper investigates an embedded block image coding technique called the "LHAD" based on the algorithm. The results show that lossless compression ratios close to the state of the art can be achieved, but that techniques such as CALIC and S+P still perform better.

Applications such as printing on demand and personalized printing have arisen where lossless halftone image compression can be useful for increasing transmission speed and lowering storage costs. We present an improvement on the context modeling scheme by adapting the context template to the periodic structure of the halftone image. This is a non-trivial problem for which we propose a fast close-to-optimal context template selection scheme based on the calculation and sorting of the autocorrelation function on a part of the image. For evaluating our scheme, we have also investigated the compression performance of a suboptimal approach based on an incremental exhaustive search; this approach can be used in practice for decompression but not for compression because of timing requirements. We have experimented with classical halftones of different resolutions and sizes and screened under different angles.

The huge sizes of screened colour-separated photographic images makes lossless compression very beneficial for both storage and transmission. Because of the special structure induced by the half-tone dots, the compression results obtained on the CCITT test images might not apply to high-resolution screened images and the default parameters of existing compression algorithms may not be optimal. In this paper we compare the performance of different classes of lossless coders: general-purpose one-dimensional coders, non-adaptive two-dimensional black-and-white coders and adaptive two-dimensional coders. Firstly, experiments on a set of test images screened under different conditions showed that MGBILEVEL and JBIG perform best with respect to compression efficiency; the difference with the other coders is significant. Secondly, we investigated the influence of the screening method (stochastic or classical screening) and screening resolution on the compression ratio for these techniques.

Compression of medical images is of great importance in the implementation of systems such as PACS (Picture Archival and Communication System) and teleradiology. Significant compression is only achievable by lossy methods, though distortion must be kept low to preserve all the diagnostic information. The JPEG lossy compression standard has some shortcomings, in particular block distortion. We investigated two block-based DCT transform techniques which tend to suppress the block effect, the DCT/DST coder and the LOT coder, and compared them with JPEG and an ordinary DCT coder for different types of medical images. The results show that the LOT coder performs best at all compression ratios for all kinds of investigated medical images. At very high image quality, JPEG is preferable for it requires almost the same bit rate as the LOT and is computationally less demanding.