Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures

Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs

A Study of trellis coded quantization for image compression

Trellis coded quantization has recently evolved as a powerful quantization technique in the world of lossy image compression. The aim of this thesis is to investigate the potential of trellis coded quantization in conjunction with two of the most popular image transforms today; the discrete cosine transform and the discrete wavelet trans form. Trellis coded quantization is compared with traditional scalar quantization. The 4-state and the 8-state trellis coded quantizers are compared in an attempt to come up with a quantifiable difference in their performances. The use of pdf-optimized quantizers for trellis coded quantization is also studied. Results for the simulations performed on two gray-scale images at an uncoded bit rate of 0.48 bits/pixel are presented by way of reconstructed images and the respective peak signal-to-noise ratios. It is evident from the results obtained that trellis coded quantization outperforms scalar quantization in both the discrete cosine transform and the discrete wavelet transform domains. The reconstructed images suggest that there does not seem to be any considerable gain in going from a 4-state to a 8-state trellis coded quantizer. Results also suggest that considerable gain can be had by employing pdf-optimized quantizers for trellis coded quantization instead of uniform quantizers

Quantization Watermarking for Joint Compression and Data Hiding Schemes

International audienceEnrichment and protection of JPEG2000 images is an important issue. Data hiding techniques are a good solution to solve these problems. In this context, we can consider the joint approach to introduce data hiding technique into JPEG2000 coding pipeline. Data hiding consists of imperceptibly altering multimedia content, to convey some information. This process is done in such a way that the hidden data is not perceptible to an observer. Digital watermarking is one type of data hiding. In addition to the imperceptibility and payload constraints, the watermark should be robust against a variety of manipulations or attacks. We focus on trellis coded quantization (TCQ) data hiding techniques and propose two JPEG2000 compression and data hiding schemes. The properties of TCQ quantization, defined in JPEG2000 part 2, are used to perform quantization and information embedding during the same time. The first scheme is designed for content description and management applications with the objective of achieving high payloads. The compression rate/imperceptibility/payload trade off is our main concern. The second joint scheme has been developed for robust watermarking and can have consequently many applications. We achieve the better imperceptibility/robustness trade off in the context of JPEG2000 compression. We provide some experimental results on the implementation of these two schemes

An efficient system for reliably transmitting image and video data over low bit rate noisy channels

This research project is intended to develop an efficient system for reliably transmitting image and video data over low bit rate noisy channels. The basic ideas behind the proposed approach are the following: employ statistical-based image modeling to facilitate pre- and post-processing and error detection, use spare redundancy that the source compression did not remove to add robustness, and implement coded modulation to improve bandwidth efficiency and noise rejection. Over the last six months, progress has been made on various aspects of the project. Through our studies of the integrated system, a list-based iterative Trellis decoder has been developed. The decoder accepts feedback from a post-processor which can detect channel errors in the reconstructed image. The error detection is based on the Huber Markov random field image model for the compressed image. The compression scheme used here is that of JPEG (Joint Photographic Experts Group). Experiments were performed and the results are quite encouraging. The principal ideas here are extendable to other compression techniques. In addition, research was also performed on unequal error protection channel coding, subband vector quantization as a means of source coding, and post processing for reducing coding artifacts. Our studies on unequal error protection (UEP) coding for image transmission focused on examining the properties of the UEP capabilities of convolutional codes. The investigation of subband vector quantization employed a wavelet transform with special emphasis on exploiting interband redundancy. The outcome of this investigation included the development of three algorithms for subband vector quantization. The reduction of transform coding artifacts was studied with the aid of a non-Gaussian Markov random field model. This results in improved image decompression. These studies are summarized and the technical papers included in the appendices

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

An overview of JPEG 2000

JPEG-2000 is an emerging standard for still image compression. This paper provides a brief history of the JPEG-2000 standardization process, an overview of the standard, and some description of the capabilities provided by the standard. Part I of the JPEG-2000 standard specifies the minimum compliant decoder, while Part II describes optional, value-added extensions. Although the standard specifies only the decoder and bitstream syntax, in this paper we describe JPEG-2000 from the point of view of encoding. We take this approach, as we believe it is more amenable to a compact description more easily understood by most readers.

Wavelet-based distributed source coding of video

Publication in the conference proceedings of EUSIPCO, Antalya, Turkey, 200

High ratio wavelet video compression through real-time rate-distortion estimation.

Thesis (M.Sc.Eng.)-University of Natal, Durban, 2003.The success of the wavelet transform in the compression of still images has prompted an expanding effort to exercise this transform in the compression of video. Most existing video compression methods incorporate techniques from still image compression, such techniques being abundant, well defined and successful. This dissertation commences with a thorough review and comparison of wavelet still image compression techniques. Thereafter an examination of wavelet video compression techniques is presented. Currently, the most effective video compression system is the DCT based framework, thus a comparison between these and the wavelet techniques is also given. Based on this review, this dissertation then presents a new, low-complexity, wavelet video compression scheme. Noting from a complexity study that the generation of temporally decorrelated, residual frames represents a significant computational burden, this scheme uses the simplest such technique; difference frames. In the case of local motion, these difference frames exhibit strong spatial clustering of significant coefficients. A simple spatial syntax is created by splitting the difference frame into tiles. Advantage of the spatial clustering may then be taken by adaptive bit allocation between the tiles. This is the central idea of the method. In order to minimize the total distortion of the frame, the scheme uses the new p-domain rate-distortion estimation scheme with global numerical optimization to predict the optimal distribution of bits between tiles. Thereafter each tile is independently wavelet transformed and compressed using the SPIHT technique. Throughout the design process computational efficiency was the design imperative, thus leading to a real-time, software only, video compression scheme. The scheme is finally compared to both the current video compression standards and the leading wavelet schemes from the literature in terms of computational complexity visual quality. It is found that for local motion scenes the proposed algorithm executes approximately an order of magnitude faster than these methods, and presents output of similar quality. This algorithm is found to be suitable for implementation in mobile and embedded devices due to its moderate memory and computational requirements