This paper describes how an infrastructure can be built for automating workflows in content production using a service oriented architecture (SOA). We fully adopted the SOA and the Business Process Management (BPM) vision in which stand-alone services provide modular functionality, service invocations are being orchestrated by a process engine, and human interaction is possible in the business processes through human tasks. We aimed at increased efficiency and control, shorter setup times, and increased flexibility. Our architecture is illustrated with a use case in which we automated a process that deals with the intake, review, transcoding and publishing of user-generated content.

The number of networked multimedia platforms that are introduced into the market has increased dramatically in recent years. Current approaches to multimedia distribution do not scale to this growing set of client configurations and heterogeneous dynamic networks. We propose a distributed architecture that offers a scalable solution to multimedia publication and distribution in such heterogeneous environments. It builds upon recent standardization efforts related to Web services. This paper details the multimedia Web services at the proxy server, that cooperate on a loosely coupled basis to tailor content creators' multimedia presentations to clients' environments. The experiments show that our Web service-oriented architecture offers a significant added value in heterogeneous multimedia environments.

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.

Summary form only given. An evaluation is made of different approaches to removing interframe redundancies. The test images we used are the MRI and CT images available from the Visual Human Project. Firstly, we found that linear predictive techniques are not able to provide any compression improvement. Even an optimal linear predictor (least-squares optimization), which holds pixels from the current and the previous frames, does not outperform the very simple 2D lossless JPEG predictor number 7. However nonlinear techniques, such as context-modeling do yield better results. In a simple experiment, lossless JPEG was estimated to code intraframe prediction errors using an interframe context. The context for coding the current pixel is formed by the magnitude of the prediction error of the corresponding pixel in the previous frame. Note that this prediction error comes from the intraframe prediction step in the previous frame. Using this interframe context-modeling approach, a reduction of the bit rate of up to 1 bit per pixel is obtainable. It is obvious that the context serves as an edge-detector, albeit a very simple and straightforward one. A new technique is proposed based on the 2D lossless image compressor JPEG-LS. The existing context-modeling scheme is extended to also catch the interframe redundancies. The interframe context is very similar to the abovementioned one, however the sign of the prediction error in the previous frame is also used.

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.

Summary form only given. In the pre-press industry color images have both a high spatial and a high color resolution. Such images require a considerable amount of storage space and impose long transmission times. Data compression is desired to reduce these storage and transmission problems. Because of the high quality requirements in the pre-press industry only lossless compression is acceptable. Most existing lossless compression schemes operate on gray-scale images. In this case the color components of color images must be compressed independently. However, higher compression ratios can be achieved by exploiting inter-color redundancies. We present a new technique for exploiting inter-component redundancies. The technique is based on a modified Karhunen-Loeve transform (KLT) scheme in combination with a novel quantization scheme that guarantees losslessness. The KLT decorrelates the color components. It is recomputed on a block by block basis and is therefore spatially adaptive. Spatial redundancies are removed using predictive techniques (lossless JPEG predictor no. 7 and the CALIC-predictor). The data which remains after the (spatial and color) decorrelation should be entropy-coded, but in the current implementation of our scheme only the entropy of the remaining data is computed. Note that in each block some block-dependent information must be sent, such as entropy-coder initialization information and KLT-descriptors (i.e., the rotation angles of the orthogonal KLT-matrix).