Two systems are presented for compression of hyperspectral imagery. These systems utilize adaptive classification, trellis-coded quantization, and optimal rate allocation. In the first system, DPCM is used for spectral decorrelation, while an adaptive wavelet-based coding scheme is used for spatial decorrelation. The second system uses DPCM in conjunction with an adaptive DCT-based coding schem...

In this work, we propose a hybrid vector quantization scheme for general images that aims at exploiting similarities among detail signals in a multiresolution decomposition of the image. In a multiresolution decomposition, the image is decomposed into a set of subbands which are localized in scale, orientation and space. Our coding scheme consists of dividing each subimage of the multiresolutio...

Subband coding is becoming a viable compression method for video transmission, since the subband system can be eeciently split into a base layer and an enhancement layer without incurring any overhead. This is desirable in ATM and other packet networks. The base layer can be a standard coding algorithm such as H.261 or MPEG. In a subband-based video coding system, the higher-frequency subbands ...

The design of a low complexity joint source channel codec for images using trellis coded quantization and convolutional codes is studied. It is shown that a low complexity joint source channel codec offering high robustness is enabled by using the same Ungerboeck trellis code to do both quantization and convolutional coding. Simulation results are presented for joint source channel coding of Ga...

We address the problem of distributed source coding using a practical and constructive approach 1], referred to as Distributed source coding using syndromes (DISCUS), with applications to sensor networks. We propose low complexity encoding and decoding methods based on linear codes, to achieve all points in the achievable rate region of Slepian-Wolf 2] problem. The extension of these concepts t...

Optimal vector quantization of variable-dimension vectors in principle is feasible by using a set of fixed dimension VQ codebooks. However, for typical applications, such a multi-codebook approach demands a grossly excessive and impractical storage and computational complexity. Efficient quantization of such variable-dimension spectral shape vectors is the most challenging and difficult encodin...

The Multi Input and Multi Output (MIMO) systems have been analyzed with a number of quantization techniques. In this short communication, few problems like performance and accuracy are investigated through a quantization technique based on Stiefel Manifold (SM). In order to improve these problems, suitable Trellis Coded Quantization (TCQ) based on Unit Memory (UM) coding is studied and applied ...

In this paper, we describe a Trellis Coded Quantization (TCQ)-based quantization and watermarking technique in the framework of JPEG2000 still image compression. Furthermore, we investigate the design of a novel joint compression and watermarking scheme based on a hybrid TCQ module which can perform at the same time quantization and watermark embedding. The watermark extraction process can be a...

This paper proposes a practical coding scheme for the Slepian-Wolf problem of separate encoding of correlated sources. Finite-state machine (FSM) encoders, concatenated in parallel, are used at the transmit side and an iterative turbo decoder is applied at the receiver. Simulation results of system performance are presented for binary sources with different amounts of correlation. Obtained resu...

This correspondence considers multiple-input single-output (MISO) wireless systems with equal gain transmission (EGT) at the transmitter and maximum ratio combining (MRC) at the receiver. In such systems, the receiver feedbacks the elemental phases of beam-forming vectors to the transmitter. Due to finite feedback rate, the elemental phases of beam-forming vectors have to be quantized effective...