Hyperspectral image compression : adapting SPIHT and EZW to Anisotropic 3-D Wavelet Coding

Hyperspectral images present some specific characteristics that should be used by an efficient compression system. In compression, wavelets have shown a good adaptability to a wide range of data, while being of reasonable complexity. Some wavelet-based compression algorithms have been successfully used for some hyperspectral space missions. This paper focuses on the optimization of a full wavelet compression system for hyperspectral images. Each step of the compression algorithm is studied and optimized. First, an algorithm to find the optimal 3-D wavelet decomposition in a rate-distortion sense is defined. Then, it is shown that a specific fixed decomposition has almost the same performance, while being more useful in terms of complexity issues. It is shown that this decomposition significantly improves the classical isotropic decomposition. One of the most useful properties of this fixed decomposition is that it allows the use of zero tree algorithms. Various tree structures, creating a relationship between coefficients, are compared. Two efficient compression methods based on zerotree coding (EZW and SPIHT) are adapted on this near-optimal decomposition with the best tree structure found. Performances are compared with the adaptation of JPEG 2000 for hyperspectral images on six different areas presenting different statistical properties

Wavelet-Based Embedded Rate Scalable Still Image Coders: A review

Embedded scalable image coding algorithms based on the wavelet transform have received considerable attention lately in academia and in industry in terms of both coding algorithms and standards activity. In addition to providing a very good coding performance, the embedded coder has the property that the bit stream can be truncated at any point and still decodes a reasonably good image. In this paper we present some state-of-the-art wavelet-based embedded rate scalable still image coders. In addition, the JPEG2000 still image compression standard is presented.

VLSI implementation of a massively parallel wavelet based zerotree coder for the intelligent pixel array

In the span of a few years, mobile multimedia communication has rapidly become a significant area of research and development constantly challenging boundaries on a variety of technologic fronts. Mobile video communications in particular encompasses a number of technical hurdles that generally steer technological advancements towards devices that are low in complexity, low in power usage yet perform the given task efficiently. Devices of this nature have been made available through the use of massively parallel processing arrays such as the Intelligent Pixel Processing Array. The Intelligent Pixel Processing array is a novel concept that integrates a parallel image capture mechanism, a parallel processing component and a parallel display component into a single chip solution geared toward mobile communications environments, be it a PDA based system or the video communicator wristwatch portrayed in Dick Tracy episodes. This thesis details work performed to provide an efficient, low power, low complexity solution surrounding the massively parallel implementation of a zerotree entropy codec for the Intelligent Pixel Array

Wavelet-Based Audio Embedding & Audio/Video Compression

With the decline in military spending, the United States relies heavily on state side support. Communications has never been more important. High-quality audio and video capabilities are a must. Watermarking, traditionally used for copyright protection, is used in a new and exciting way. An efficient wavelet-based watermarking technique embeds audio information into a video signal. Several highly effective compression techniques are applied to compress the resulting audio/video signal in an embedded fashion. This wavelet-based compression algorithm incorporates bit plane coding, first difference coding, and Huffman coding. To demonstrate the potential of this audio embedding audio/video compression system, an audio signal is embedded into a video signal and the combined signal is compressed. Results show that overall compression rates of 15:1 can be achieved. The video signal is reconstructed with a median PSNR of nearly 33dB. Finally, the audio signal is extracted with out error

Image Compression by Wavelet Transform.

Digital images are widely used in computer applications. Uncompressed digital images require considerable storage capacity and transmission bandwidth. Efficient image compression solutions are becoming more critical with the recent growth of data intensive, multimedia-based web applications. This thesis studies image compression with wavelet transforms. As a necessary background, the basic concepts of graphical image storage and currently used compression algorithms are discussed. The mathematical properties of several types of wavelets, including Haar, Daubechies, and biorthogonal spline wavelets are covered and the Enbedded Zerotree Wavelet (EZW) coding algorithm is introduced. The last part of the thesis analyzes the compression results to compare the wavelet types

Zerotree-based stereoscopic video CODEC

Due to the provision of a more natural representation of a scene in the form of left and right eye views, a stereoscopic imaging system provides a more effective method for image/video display. Unfortunately the vast amount of information that must be transmitted/stored to represent a stereo image pair/video sequence, has so far hindered its use in commercial applications. However, by properly exploiting the spatial, temporal and binocular redundancy, a stereo image pair or a sequence could be compressed and transmitted through a single monocular channel’s bandwidth without unduly sacrificing the perceived stereoscopic image quality. We propose a timely and novel framework to transmit stereoscopic data efficiently. We propose a timely and novel framework to transmit stereoscopic data efficiently. We present a new technique for coding stereo video sequences based on discrete wavelet transform DWT technology. The proposed technique particularly exploits zerotree entropy ZTE coding that makes use of the wavelet block concept to achieve low bit rate stereo video coding. One of the two image streams, namely, the main stream, is independently coded by a zerotree video CODEC, while the second stream, namely, the auxiliary stream, is predicted based on disparity compensation. A zerotree video CODEC subsequently codes the residual stream. We compare the performance of the proposed CODEC with a discrete cosine transform DCT -based, modified MPEG-2 stereo video CODEC. We show that the proposed CODEC outperforms the benchmark CODEC in coding both main and auxiliary streams

High-Performance Embedded Morphological Wavelet Coding

Morphological analysis can be applied in wavelet domain to analyze and represent the position of significant coefficients. New operators have to be introduced which are able to exploit both the multiresolution and the filter bank peculiarities of the subband representation of visual information. In this paper an efficient morphological wavelet coder is proposed. The clustering trend of significant coefficients is captured by a new kind of multi resolution binary dilation operator. The layered and adaptive nature of this subband dilation makes it possible for the coding technique to produce an embedded bit-stream with a modest computational cost and state-of-the-art Rate-Distortion performance. Morphological wavelet coding appears promising because the localized analysis of wavelet coefficient clusters is adequate to capture intrinsic patterns of the source which can have substantial benefits for perceptual or even object-based reconstruction quality concerns. Here we test the performance of our algorithm and compare the effects of different wavelet filters. We obtain state of the art coding performance and good perceptual results both for 2D and 3D images, with a new technique that seems to be well suited for further developments

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