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Abstract - IMDSP3

IMDSP3.1	An Embedded DCT-Based Still Image Coding Algorithm D. Nister, C. Christopoulos (Ericsson Telecom AB, Sweden) In this paper, an embedded DCT-based image coding algorithm is described. The decoder can cut the bitstream at any point and therefore reconstruct an image at lower rate. The quality of the reconstructed image at this lower rate would be the same as if the image was coded directly at that rate. The algorithm outperforms any other DCT-based coders published in the literature, including the JPEG algorithm. Moreover, our DCT-based embedded image coder gives results close to the best wavelet-based coders. The algorithm is very useful in various applications, like WWW, fast browsing of databases, etc.
IMDSP3.2	On the Trade-Off between Contour-Adaptive Texture Coding and Lossy Shape Coding K. Schroeder (University of Dortmund, Germany) Shape-adaptive texture coding is often being perceived as a mean to achieve increased coding efficiency, e.g. due to a better presentation of correlation properties along the boundary between two objects which should lead to a higher transfrom gain. However, if data rates demand a lossy encoding of contours, an improvement in transform gain becomes questionable. This paper investigates the potential coding gain which may result from shape-adaptive texture coding using DCT basis functions under the constraint of both lossless and lossy shape coding. For this purpose, a 1D texture model is derived with reflects synthetical as well as "natural" borders between objects.
IMDSP3.3	A Fast Encoding Method without Search for Fractal Image Compression I. Kim, R.-H. Park (Sogang University, Korea) A fast coding algorithm for images using vector quantization (VQ) and pixelwise fractal approximation is proposed. The low frequency component of an input image is approximated and its residual is used to calculate the scaling factor of fractal transform. The scaling factor is compressed by transform VQ (TVQ). In the proposed method, to encode a digital image by an iterated function system (IFS), we use the pixel-based IFS (PIFS) rather than the block-based IFS: the scaling factor is computed for each pixel. In the proposed method, the scaling factor of each pixel is calculated with the constraint of contraction mapping and it is transformed by wavelet and quantized by VQ. For approximation of an original image, the variable block-size segmentation using quadtree is employed. Because the proposed method calculates the scaling factor using the PIFS, the encoding time is faster than the conventional algorithm using block-based IFS with search.
IMDSP3.4	Adaptive-Rate Image Compression for Wireless Digital Data Transmission Systems J. Kleider, G. Abousleman (Motorola SSTG, USA) The vast amount of data needed to represent digital imagery motivates the use of advanced compression systems to reduce the bandwidth required to transmit high-resolution source imagery. We propose two methods to provide optimal image quality at a fixed image delivery rate. The first method, channel-controlled variable-rate (CCVR) image coding, operates within the constraint that the modulation symbol rate is fixed. The second method, adaptive-rate coding-modulation (ARCM), utilizes adaptive modulation, and is less complex, while providing increased performance. Both methods use a variable-compression-ratio image coder and variable-rate channel coding. The objective is to maximize the quality of the reconstructed image at the reciever for Rayleigh fading and AWGN. The ARCM system achieves up to a 17 dB improvement over the peak signal-to-noise ratio performance of a system designed assuming a fixed-compression-ratio image coder and fixed-rate channel coding.
IMDSP3.5	JPEG Compliant Efficient Progressive Image Coding J. In, S. Shirani, F. Kossentini (University of British Columbia, Canada) Among the different modes of operations allowed in the current JPEG standard, the sequential and progressive modes are the most widely used. While the sequential JPEG mode yields essentially the same level of compression performance for most encoder implementations, the performance of progressive JPEG depends highly upon the designed encoder structure. This is due to the flexibility the standard leaves open in designing progressive JPEG encoders. In this paper, a rate-distortion optimized JPEG compliant encoder is presented that produces a sequence of bit scans, ordered in terms of decreasing importance. Our encoder outperforms a baseline JPEG encoder in terms of compression, significantly at medium and high bit rates, and substantially at low bit rates. Moreover, unlike baseline JPEG encoders, ours can achieve precise rate/distortion control. Good rate-distortion performance at low bit rates and precise rate control, provided by our progressive JPEG compliant encoder, are two highly desired features currently sought for JPEG-2000.
IMDSP3.6	A Low Bit Rate Segmented Video Codec with Hybrid Motion Estimation and Inherent Bit Rate Control Capability V. Christopoulos, J. Cornelis (Vrije Universiteit Brussel, Belgium) In this paper a segmented video codec with hybrid motion estimation and inherent bit rate control capability is presented. The first frame in the data is always encoded in intraframe mode, while the rest of the frames are encoded in interframe mode. The interframe encoding is based on (1) hybrid conventional/perspective block motion vector estimation and coding, and (2) coding of the prediction error (Displaced Frame Difference, "DFD") using segmented image coding techniques. We present a way to partition the DFD in moving and static regions and we explain how this classification strategy can be used as a means to control the bit rate. The simulation results show that the hybrid motion estimation technique outperforms the conventional full search block-matching method by improving the overall PSNR for reduced bit rate, and that the bit rate control strategy, although simple, is very efficient for monitoring both the bit rate and the quality degradation.
IMDSP3.7	Rank Order Polynomial Decomposition for Image Compression E. Olivier, G. Reto, V. Jean-Marc, K. Murat (Swiss Federal Institute of Technology, Switzerland) In this paper, a novel decomposition scheme for image compression is presented. It is capable to apply any nonlinear model to compress images in a lossless way. Here, a very efficient polynomial model that considers spatial information as well as order statistic information is introduced. This new rank order polynomial decomposition (ROPD) that allows also for a progressive bitstream is applied to various images of different nature and compared to the morphological subband decomposition (MSD) and to the best prediction mode for lossless compression of the international standard JPEG. For all compressed images, ROPD provides better compression results than MSD and clearly outperforms the lossless mode of JPEG.
IMDSP3.8	Bit Error Prediction for Digital Image Data J. Trelewicz, D. Cochran (Arizona State University, USA) A nonideal two-dimensional optical system, as encountered in digital holographic data storage applications, can modify the intensity of transmitted digital data through beam shaping, focal surface distortion, and moire patterns. Such changes in intensity can have significant adverse effects on digital data recovery at the receiver (e.g., a CCD camera). Current research seeks to detect and correct classes of such distortion so that recovery methods can be applied to the received data. This paper discusses methods used to predict the locations of bit errors in the recovered data. Prediction information may be used as weighting information in the recovery algorithm and in the design of channel codes. Furthermore, the higher the level of distortion that can be tolerated in the system, the lower the cost of the corresponding lenses, making the system more tractable for commercialization.
IMDSP3.9	Joint Compression and Restoration of Images Using Wavelets and Non-Linear Interpolative Vector Quantization K. Panchapakesan, A. Bilgin, M. Marcellin, B. Hunt (University of Arizona, USA) In this paper, we present a wavelet based non-linear interpolative vector quantization scheme for joint compression and restoration of images; two tasks which are traditionally regarded as having conflicting goals. Vector quantizer codebook training is done using a training set consisting of pairs of the original image and its diffraction-limited counterpart. The designed VQ is then used to compress and simultaneously restore diffraction-limited images. Results from simulations indicate that the image produced at the output of the decoder is quantitatively and visually superior to the diffraction-limited image at the input to the encoder. We also compare the performance of several wavelet filters in our algorithm.
IMDSP3.10	Comparative Investigation of A Non-Linear Predictive Codec versus JPEG Lossless Compression Mode J. Jiang, M. Lo (Loughborough University, UK) A non-linear predictive coding based algorithm is proposed in the paper for lossless image compression. The algorithm uses two neighbouring pixels, one left and the other top, as a pioneering block to search for the best matched blocks inside a pre-defined window. The corresponding pixels associated with the best matched blocks are then taken to produce the predictive value, together with the two pioneering pixels. Comparative investigation is carried out by experiments which show clearly that the proposed algorithm constantly outperform JPEG lossless compression mode.

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