50 research outputs found

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

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    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

    A Study of image compression based transmission algorithm Using SPIHT for low bit rate application

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    Image compression is internationally recognized up to the minute tools for decrease the communication bandwidth and save the transmitting power. It should reproduce a good quality image after compression at low bit rates. Set partitioning in hierarchical trees (SPIHT) is wavelet based computationally very fast and among the best image compression based transmission algorithm that offers good compression ratios, fast execution time and good image quality. Precise Rate Control (PRC) is the distinct characteristic of SPIHT. Image compression-based on Precise Rate Control and fast coding time are principally analyzed in this paper. Experimental result shows that, in the case of low bit-rate, the modified algorithm with fast Coding Time and Precise Rate Control can reduce the execution time and improves the quality of reconstructed image in both PSNR and perceptual when compare to at the same low bit rate

    An efficient technique for lossless address data compression using adaptive SPIHT Algorithm in WSN

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    The computer is becoming more and more powerful day by day. Data compression is a popular approach to reducing data volumes and hence lowering disk I/O and network data transfer times. While several lossy data compression techniques have demonstrated excellent compression ratios, lossless data compression techniques are still among the most popular ones. Sensor networks represent a non-traditional source of information, as readings generated by sensors flow continuously, leading to an infinite stream of data. Sensors are non-reactive elements which are used to monitor real life phenomena, such as live weather conditions, network traffic, etc. They are usually organized into networks where their readings are transmitted using low level protocols

    MEDICAL IMAGES COMPRESSION BASED ON SPIHT AND BAT INSPIRED ALGORITHMS

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    There is a significant necessity to compress the medical images for the purposes of communication and storage.Most currently available compression techniques produce an extremely high compression ratio with a high-quality loss. Inmedical applications, the diagnostically significant regions (interest region) should have a high image quality. Therefore, it ispreferable to compress the interest regions by utilizing the Lossless compression techniques, whilst the diagnostically lessersignificant regions (non-interest region) can be compressed by utilizing the Lossy compression techniques. In this paper, a hybridtechnique of Set Partition in Hierarchical Tree (SPIHT) and Bat inspired algorithms have been utilized for Lossless compressionthe interest region, and the non-interest region is loosely compressed with the Discrete Cosine Transform (DCT) technique.The experimental results present that the proposed hybrid technique enhances the compression performance and ratio. Also,the utilization of DCT increases compression performance with low computational complexity

    Multi-resolution adaptation of the SPIHT algorithm for multiple description

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    Multiple description codes are data compression algorithms designed with the goal of minimizing the distortion caused by data loss in packet-based or diversity communications systems. Recently, techniques that achieve multiple description coding by combining embedded source codes with unequal error protection channel codes have become popular in the literature. These codes allow for data reconstruction with any subset of the transmitted packets and achieve progressively better source reconstructions as more and more packets are decoded. The given methods may be applied to any embedded source description. While applicability to all embedded source codes provides great flexibility, this separation approach begs the question of whether better performance could be achieved by taking advantage of the internal structure of a particular embedded code. In this paper, we investigate an extremely simple method for using an embedded source code's internal state information in the construction of a multiple description code. In particular, we protect an embedded SPIHT bitstream by adding to that bitstream periodic descriptions of state information from the encoder, and we demonstrate how the state information can be used to recover lost bits. For low probabilities of network packet loss, the proposed algorithm achieves performance within 0.35 dB of the performance of a more sophisticated channel coding algorithm when both algorithms are applied to same SPIHT embedded source code

    Variable Block Size Motion Compensation In The Redundant Wavelet Domain

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    Video is one of the most powerful forms of multimedia because of the extensive information it delivers. Video sequences are highly correlated both temporally and spatially, a fact which makes the compression of video possible. Modern video systems employ motion estimation and motion compensation (ME/MC) to de-correlate a video sequence temporally. ME/MC forms a prediction of the current frame using the frames which have been already encoded. Consequently, one needs to transmit the corresponding residual image instead of the original frame, as well as a set of motion vectors which describe the scene motion as observed at the encoder. The redundant wavelet transform (RDWT) provides several advantages over the conventional wavelet transform (DWT). The RDWT overcomes the shift invariant problem in DWT. Moreover, RDWT retains all the phase information of wavelet coefficients and provides multiple prediction possibilities for ME/MC in wavelet domain. The general idea of variable size block motion compensation (VSBMC) technique is to partition a frame in such a way that regions with uniform translational motions are divided into larger blocks while those containing complicated motions into smaller blocks, leading to an adaptive distribution of motion vectors (MV) across the frame. The research proposed new adaptive partitioning schemes and decision criteria in RDWT that utilize more effectively the motion content of a frame in terms of various block sizes. The research also proposed a selective subpixel accuracy algorithm for the motion vector using a multiband approach. The selective subpixel accuracy reduces the computations produced by the conventional subpixel algorithm while maintaining the same accuracy. In addition, the method of overlapped block motion compensation (OBMC) is used to reduce blocking artifacts. Finally, the research extends the applications of the proposed VSBMC to the 3D video sequences. The experimental results obtained here have shown that VSBMC in the RDWT domain can be a powerful tool for video compression

    Low Bit-rate Color Video Compression using Multiwavelets in Three Dimensions

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    In recent years, wavelet-based video compressions have become a major focus of research because of the advantages that it provides. More recently, a growing thrust of studies explored the use of multiple scaling functions and multiple wavelets with desirable properties in various fields, from image de-noising to compression. In term of data compression, multiple scaling functions and wavelets offer a greater flexibility in coefficient quantization at high compression ratio than a comparable single wavelet. The purpose of this research is to investigate the possible improvement of scalable wavelet-based color video compression at low bit-rates by using three-dimensional multiwavelets. The first part of this work included the development of the spatio-temporal decomposition process for multiwavelets and the implementation of an efficient 3-D SPIHT encoder/decoder as a common platform for performance evaluation of two well-known multiwavelet systems against a comparable single wavelet in low bitrate color video compression. The second part involved the development of a motion-compensated 3-D compression codec and a modified SPIHT algorithm designed specifically for this codec by incorporating an advantage in the design of 2D SPIHT into the 3D SPIHT coder. In an experiment that compared their performances, the 3D motion-compensated codec with unmodified 3D SPIHT had gains of 0.3dB to 4.88dB over regular 2D wavelet-based motion-compensated codec using 2D SPIHT in the coding of 19 endoscopy sequences at 1/40 compression ratio. The effectiveness of the modified SPIHT algorithm was verified by the results of a second experiment in which it was used to re-encode 4 of the 19 sequences with lowest performance gains and improved them by 0.5dB to 1.0dB. The last part of the investigation examined the effect of multiwavelet packet on 3-D video compression as well as the effects of coding multiwavelet packets based on the frequency order and energy content of individual subbands

    Real-time scalable video coding for surveillance applications on embedded architectures

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