Long-term memory prediction extends the spatial displacement vector utilized in hybrid video coding by a variable time delay permitting the use of more than one reference frame for motion compensation. This extension provides improved rate-distortion performance. However, motion compensation in combination with transmission errors leads to temporal error propagation that occurs when the reference frames at encoder and decoder dier. In this paper, we present a framework that incorporates an error estimate into rate-constrained motion estimation and mode decision. Experimental results with a Rayleigh fading channel show that long-term memory motion compensation signicantly outperforms single-frame prediction. 1. INTRODUCTION The eciency of long-term memory motion-compensated prediction (MCP) as an approach to improve coding performance has been demonstrated in [1]. The ITU-T has decided to adopt this feature as Annex U to version 3 of the H.263 standard. In this paper, we show that t...

IEEE Transactions on Image Processing This paper presents novel coding algorithms based on tree structured segmentation, which achieve the correct asymptotic rate-distortion (R-D) behavior for a simple class of signals, known as piecewise poly-nomials, by using an R-D based prune and join scheme. For the one dimensional (1-D) case, our scheme is based on binary tree segmentation of the signal. This scheme approximates the signal segments using polynomial models and utilizes an R-D optimal bit allocation strategy among the different signal segments. The scheme further encodes similar neighbors jointly to achieve the correct exponentially decaying R-D behavior � D(R) ∼ c02 −c1R � , thus improving over classic wavelet schemes. We also prove that the com-putational complexity of the scheme is of O (N log N). We then show the extension of this scheme to the two dimensional (2-D) case using a quadtree. This quadtree coding scheme also achieves an exponentially decaying R-D behavior, for the polygonal image model composed of a white polygon shaped object against a uniform black background, with low computational cost of O (N log N). Again, the key is an R-D opti-mized prune and join strategy. Finally, we conclude with numerical results, which show that the proposed quadtree coding scheme outperforms JPEG2000 by about 1 dB for real images, like cameraman, at low rates of around 0.15 bpp.

The increased popularity of multimedia applications places a great demand on efficient data storage and transmission techniques. Network communication, especially over a wireless network, can easily be intercepted and must be protected from eavesdroppers. Unfortunately, encryption and decryption are slow and it is often difficult, if not impossible, to carry out real-time secure image and video communication and processing. Methods have been proposed to combine compression and encryption together to reduce the overall processing time [3, 4, 12, 18, 20], but they are either insecure or too computationally intensive. We propose a novel solution, called partial encryption, in which a secure encryption algorithm is used to encrypt only part of the compressed data. Partial encryption is applied to several image and video compression algorithms in this paper. Only 13%--27% of the output from quadtree compression algorithms [13, 17, 29, 30, 31, 32] is encrypted for typical images, and less than 2% is encrypted for 512 \Theta 512 images compressed by the SPIHT algorithm [26]. The results are similar for video compression, resulting in a significant reduction in encryption and decryption time. The proposed partial encryption schemes are fast, secure, and do not reduce the compression performance of the underlying compression algorithm. EDICS Number: SP 7.8 This research is supported in part by the Motorola Wireless Data Group and the Canadian Natural Sciences and Engineering Research Council under Grant OGP9198 and Postgraduate Scholarship. y Presently at Department of Computer Science, University of Waterloo. z To whom correspondence should be addressed. 1 1

In object-based video, the encoding of the video data is decoupled into the encoding of shape, motion and texture information, which enables certain functionalities like content-based interactivity and scalability. However, the problem of how to jointly encode these separate signals to reach the best coding efficiency has never been solved thoroughly. In this paper, we present an operational ratedistortion optimal bit allocation scheme that provides a solution to this problem. Our approach is based on the Lagrangian relaxation and dynamic programming. Experimental results indicate that the proposed optimal encoding approach has considerable gains over an ad-hoc method without optimization. Furthermore the proposed algorithm is much more efficient than exhaustive search. 1.

We address the problem of optimal forward--adaptive quantization in the video and image coding framework. In this framework, as is consistent with that of most practical coders like MPEG, the encoder has the capability of changing the quantizer periodically (e.g. at a macroblock interval in MPEG). In this paper, we formulate an optimal strategy, based on dynamic programming, for updating the quantizer choice for coding an image or video signal. While in some coding environments the overhead needed to specify the quantizer used by each block is equal for every choice of quantizer, in other situations (e.g. MPEG) the overhead cost is higher if the quantizer changes from one block to the next. We concentrate on the latter case which will be more likely encountered in situations where the overhead represents a significant fraction of the overall rate, as can be the case if a low bit rate is used (e.g. error frames in a typical motion-compensated video coder). We provide empirical evidence ...

ABSTRACT: Lossless image compression with progressive transmission capabilities plays a key role in measurement applications, requiring quantitative analysis and involving large sets of images. This work proposes a wavelet-based compression scheme that is able to operate in the lossless mode. The quantization module implements a new technique for the coding of the wavelet coefficients that is more effective than the classical zerotree coding. The experimental results obtained on a set of multimodal medical images show that the proposed algorithm outperforms the embedded zerotree coder combined with the integer wavelet transform by 0.28 bpp, the set-partitioning coder by 0.1 bpp, and the lossless JPEG coder by 0.6 bpp. The scheme produces a losslessly compressed embedded data stream; hence, it supports progressive refinement of the decompressed images. Therefore, it is a good candidate for telematics applications requiring fast user interaction with the image data, retaining the option of lossless transmission and archiving of the

: A fractal coder partitions an image into blocks that are coded via self-references to other parts of the image itself. In this paper we present a fractal coder that derives highly imageadaptive partitions and corresponding fractal codes in a time-efficient manner using a regionmerging approach. The proposed merging strategy leads to improved rate-distortion performance compared to previously reported pure fractal coders, and it is faster than other state-of-the-art fractal coding methods. Keywords: Fractal compression, image compression, image partitions, segmentation-based coding. IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. XX, NO. Y, MONTH 1999 102 I. Introduction IN fractal image compression an image is modeled as the unique fixed point of a contractive operator on the space of images. This type of image representation was first proposed by Barnsley and Sloan [1], [2] and Jacquin [3], [4] who devised the first practical fractal coder. Fractal coding has since been a topic of act...

Abstract—We address the best basis problem—or, more generally, the best representation problem: Given a signal, a dictionary of representations, and an additive cost function, the aim is to select the representation from the dictionary which minimizes the cost for the given signal. We develop a new framework of multitree dictionaries, which includes some previously proposed dictionaries as special cases. We show how to efficiently find the best representation in a multitree dictionary using a recursive tree-pruning algorithm. We illustrate our framework through several examples, including a novel block image coder, which significantly outperforms both the standard JPEG and quadtree-based methods and is comparable to embedded coders such as JPEG2000 and SPIHT. Index Terms—Best basis, grammar, image compression, JPEG. I.

Abstract — In this paper, we address the fundamental problem of optimally splitting a video sequence into two sources of information, the displaced frame difference (DFD) and the displacement vector field (DVF). We first consider the case of a lossless motion-compensated video coder (MCVC), and derive a general dynamic programming (DP) formulation which results in an optimal tradeoff between the DVF and the DFD. We then consider the more important case of a lossy MCVC, and present an algorithm which solves the tradeoff between the rate and the distortion. This algorithm is based on the Lagrange multiplier method and the DP approach introduced for the lossless MCVC. We then present an H.263-based MCVC which uses the proposed optimal bit allocation, and compare its results to H.263. As expected, the proposed coder is superior in the rate-distortion sense. In addition to this, it offers many advantages for a rate control scheme. The presented theory can be applied to build new optimal coders, and to analyze the heuristics employed in existing coders. In fact, whenever one changes an existing coder, the proposed theory can be used to evaluate how the change affects its performance. Index Terms—Motion estimation, optimal bit allocation, ratedistortion theory, quantizer selection, video compression. I.

In this paper we propose an optimal quad-tree (QT)-based motion estimator for video compression. It is optimal in the sense that for a given bit budget for encoding the displacement vector field (DVF) and the QT segmentation, the scheme finds a DVF and a QT segmentation which minimizes the energy of the resulting displaced frame difference (DFD). We find the optimal QT decomposition and the optimal DVF jointly using the Lagrangian multiplier method and a multilevel dynamic program. We introduce a new very fast convex search for the optimal Lagrangian multiplier , which results in a very fast convergence of the Lagrangian multiplier method. The resulting DVF is spatially inhomogeneous since large blocks are used in areas with simple motion and small blocks in areas with complex motion. We also propose a novel motion compensated interpolation scheme which uses the same mathematical tools developed for the QT-based motion estimator. One of the advantages of this scheme is the globally o...