In this letter, a no-reference perceptual sharpness metric based on a statistical analysis of local edge gradients is presented. The method takes properties of the human visual system into account. Based on perceptual properties, a relationship between the extracted statistical features and the metric score is established to form a Perceptual Sharpness Index (PSI). A comparison with state-of-the-art metrics shows that the proposed method correlates highly with human perception and exhibits low computational complexity. In contrast to existing metrics, the PSI performs well for a wide range of blurriness and shows a high degree of invariance for different image contents.

Automatic quality control for audiovisual media is an important tool in the media production process. In this paper we present tools for assessing the quality of audiovisual content in order to decide about the reusability of archive content. We first discuss automatic detectors for the common impairments noise and grain, video breakups, sharpness, image dynamics and blocking. For the efficient viewing and verification of the automatic results by an operator, three approaches for user interfaces are presented. Finally, we discuss the integration of the tools into a service oriented architecture, focusing on the recent standardization efforts by EBU and AMWA's Joint Task Force on a Framework for Interoperability of Media Services in TV Production (FIMS).

Summary form only given. We introduce to the surveillance community the VIRAT Video Dataset[1], which is a new large-scale surveillance video dataset designed to assess the performance of event recognition algorithms in realistic scenes1.

We present a C++ library implementing part 2, 3, 4 and 5 of the MPEG 7 multimedia content description standard, including the updated version finalized in 2004. The library supports handling of MPEG-7 descriptions as trees of typed objects, supporting (de)serialization from/to XML. It has convenient and powerful features such as creation of subtrees by XPath statements and is extensible at runtime. The library is available for Windows, Linux/Unix and Mac OS X. It has been provided under a free use license for several years, downloaded more than 5,200 times and used in a large number of projects. It has been published under GNU LGPL in 2009. This paper discusses the key functionalities of the library as well as some exemplary applications.

A significant amount of work in film and video preservation is dedicated to quality assessment of the content to be archived or reused out of the archive. This paper proposes automatic content analysis algorithms which reduce manual inspection time in software based preservation environments. We list the requirements for such algorithms and tools and show exemplarily on a freeze frame impairment detector how analysis algorithms need to be designed for meeting the requirements. The evaluation has shown that robustness against other impairments (noise and flickering) is an essential part of the algorithm. Successful detection of freeze frame impairments with a minimum length of three frames is achieved. The consideration of human perception is important to achieve low false detection rates. Analysis results are represented in a MPEG-7 standard compliant way. The proposed defect summary visualization tool enables efficient human exploration of visually impaired content.

A considerable amount of work in larger film and video restoration projects is dedicated to manually exploring the audiovisual content in order to estimate the costs for restoration and to plan the restoration. Manual exploration is a significant cost factor. In this paper we propose automatic content analysis algorithms and summarization techniques which allow the reduction of manual inspection time in a software based restoration environment. The throughput requirement for analysis of dust and other defects is reached by sparse application of the detectors in the image sequence while retaining sufficient detection accuracy. Analysis result metadata are represented in a MPEG-7 standard compliant way. The proposed defect summary visualization tools facilitate efficient exploration of visually impaired content by the user.

The knowledge of material specific film grain characteristics can significantly improve the performance of digital film processing algorithms. This paper proposes a rapid and reliable detector for film grain properties. First, homogeneous blocks concerning intensity and texture are determined by a novel measure calculated in the frequency domain. Second, based on these blocks the signal-dependent grain noise level is estimated and an image region of pure film grain is detected. Evaluation based on a wide range of structured images with high frequent electronic noise and low frequent film grain, shows that the method performs with a worst case estimation error of 2.54 dB in typical movie quality (PSNR of 25-40 dB). This meets the requirements of real applications such as digital film restoration and special effects compositing.

MPEG-7 is an excellent choice for the description of audiovisual content due to its flexibility and comprehensiveness. The drawback is that these properties also increase the complexity of descriptions and cause ambiguities which hinder interoperability. In order to partly solve these problems, profiles and levels have been proposed, but the definitions of the adopted profiles lack semantic constraints which are necessary for interoperability. We propose a profile for detailed description of audiovisual content that can be used in a broad range of applications. The profile aims at describing single multimedia content entities, allowing a comprehensive structural description of the content, including also audio and visual feature descriptions. The profile defines a set of semantic constraints on the selected tools, which resolve ambiguities in modeling the description and support system interoperability. The proposed profile has been successfully used in a wide range of applications