Scalable Object-Based Indexing of HD Videos: A JPEG2000- Oriented solution

Video indexing technique is crucial in multimedia applications. In the case of HD (High Definition) Video, the principle of scalability is of great importance. The wavelet decomposition used in the JPEG2000 standard provides this property. In this paper, we propose a scalable descriptor based on objects. First, a scalable moving object extraction method is constructed. Using the wavelet data, it relies on the combination of a robust global motion estimation with a morphological color segmentation at a low spatial resolution. It is then refined using the scalable order of data. Second, a descriptor is built only on the objects found at the previous step. This descriptor is based on multiscale histograms of wavelet coefficients of moving object

Image coding for digitized libraries

Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent Univ., 1998.Thesis (Ph.D.) -- Bilkent University, 1998.Includes bibliographical references leaves 104-113III this thesis, image coding methods for two basic image types are developed under a digitized library framework. The two image types are gray tone or color images, and binary textual images, which are the digitized image versions of text documents. The grciy tone images are encoded using an adaptive subband decomposition followed by zerotree quantizers. The adaptive sub- l)and decomposition filter bank adaptively updates the filter bank coefficients in which the values of one of the subbands is predicted from the other sub- band. It is observed that the adaptive subband decomposition performs better than a regulcir subband decomposition with a fixed filter bank in terms of compression. For the binary textual images, a compression algorithm using binary subband decomposition followed by a textual image compression (TIC) method that exploits the redundancy in repeating characters is developed. The binary subband decomposition yields binary sub-images, and the TIC method is applied to the low band sub-image. Obtaining binary sub-images improves compression results as well as pattern matching time of the TIC method. Simulation results for both adaptive subband decomposition and multiresolution TIC methods indicate improvements over the methods described in the literature.Gerek, Ömer NezihPh.D

Combined Industry, Space and Earth Science Data Compression Workshop

The sixth annual Space and Earth Science Data Compression Workshop and the third annual Data Compression Industry Workshop were held as a single combined workshop. The workshop was held April 4, 1996 in Snowbird, Utah in conjunction with the 1996 IEEE Data Compression Conference, which was held at the same location March 31 - April 3, 1996. The Space and Earth Science Data Compression sessions seek to explore opportunities for data compression to enhance the collection, analysis, and retrieval of space and earth science data. Of particular interest is data compression research that is integrated into, or has the potential to be integrated into, a particular space or earth science data information system. Preference is given to data compression research that takes into account the scien- tist's data requirements, and the constraints imposed by the data collection, transmission, distribution and archival systems

MASCOT : metadata for advanced scalable video coding tools : final report

The goal of the MASCOT project was to develop new video coding schemes and tools that provide both an increased coding efficiency as well as extended scalability features compared to technology that was available at the beginning of the project. Towards that goal the following tools would be used: - metadata-based coding tools; - new spatiotemporal decompositions; - new prediction schemes. Although the initial goal was to develop one single codec architecture that was able to combine all new coding tools that were foreseen when the project was formulated, it became clear that this would limit the selection of the new tools. Therefore the consortium decided to develop two codec frameworks within the project, a standard hybrid DCT-based codec and a 3D wavelet-based codec, which together are able to accommodate all tools developed during the course of the project

Compressed Domain Low Level Visual Descriptors

Content-based image retrieval and analysis have been developed for a long time, and various visual descriptors have been proposed. The need of multiple versions of an image spurs the development of image compression and descriptors based on compression domain. However, these descriptors are not able to achieve good performance in terms of quality and resolution scalability. As the appearance of JPEG 2000 compression standard, its coding algorithm and structure of bit stream make the scalability possible. The JPEG 2000 based descriptors can be developed to satisfy multiple compression levels, and keep a good performance even when the images are highly compressed. In this thesis, most existing famous and popular low level visual descriptors are reviewed. Image compression and some image analysis and retrieval approaches are introduced. Two JPEG 2000 based descriptors called state and context are proposed in this research, and an image retrieval system using these descriptors is constructed. Experiments are conducted and the results indicate the proposed descriptors have a good retrieval performance. State and context are further compared with industrial standard MPEG-7 descriptors and state-of-art SIFT method in multiple resolution and quality situations, and the proposed descriptors are proved to be more suitable in compression domain

Astronomical image manipulation in the transform domain

It is well known that images are usually stored and transmitted in the compressed form to save memory space and I/O bandwidth. Among many image compression schemes, transform coding is a widely used coding method. Traditionally, processing a compressed image requires decompression first. Following manipulations, the processed image is compressed again for storage. To reduce the computational complexity and processing time, manipulating images in the semi-compressed or transform domain is an efficient solution; Many astronomical images are compressed and stored by JPEG and HCOM-PRESS, which are based on the Discrete Cosine Transform (DCT) and the Discrete Wavelet Transform (DWT), respectively. In this thesis, a suite of image processing algorithms in the transform domain, DCT and DWT, is developed. In particular, new methods for edge enhancement and minimum (MIN)/maximum (MAX) gray scale intensity estimation in the DCT domain are proposed. Algebraic operations and image interpolation in the DWT domain are addressed. The superiority of new algorithms over the conventional ones is demonstrated by comparing the time complexities and qualities of the processed image in the transform domain to those in the spatial domain