Effective acquisition, analysis and reconstruction of multi-modal data such as colour and multi-/hyper-spectral imagery is crucial in smart camera applications, where wavelet-based coding and compression of images are...
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Effective acquisition, analysis and reconstruction of multi-modal data such as colour and multi-/hyper-spectral imagery is crucial in smart camera applications, where wavelet-based coding and compression of images are highly demanded. Many existing discrete wavelet filtering banks have fixed coefficients hence their performance is highly dependent on the signal/ image being processed. To tackle this problem, a unified framework is proposed in this study, which can produce a series of discrete wavelet filtering banks, where many existing discrete wavelet filtering banks become special cases of the framework. For each generated filtering bank, it consists of two decomposition filters and two reconstruction filters through an optimisation process. The efficacy of the filtering banks produced by the framework has been validated in two case studies, including colour image decomposition and reconstruction, and hyperspectral image classification. Comprehensive experiments have demonstrated the superior performance of the proposed framework, which will benefit the efficacy of smart camera and camera network applications.
In this paper, a hybrid method is proposed for multi-channel electroencephalograms (EEG) signal compression. This new method takes advantage of two different compression techniques: fractal and wavelet-based coding. F...
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In this paper, a hybrid method is proposed for multi-channel electroencephalograms (EEG) signal compression. This new method takes advantage of two different compression techniques: fractal and wavelet-based coding. First, an effective decorrelation is performed through the principal component analysis of different channels to efficiently compress the multi-channel EEG data. Then, the decorrelated EEG signal is decomposed using wavelet packet transform (WPT). Finally, fractal encoding is applied to the low frequency coefficients of WPT, and a modified wavelet-based coding is used for coding the remaining high frequency coefficients. This new method provides improved compression results as compared to the wavelet and fractal compression methods.
This paper presents the Secure Shape and Texture SPIHT (SecST-SPIHT) scheme for secure coding of arbitrarily shaped visual objects. The scheme can be employed in a privacy protected surveillance system, whereby visual...
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This paper presents the Secure Shape and Texture SPIHT (SecST-SPIHT) scheme for secure coding of arbitrarily shaped visual objects. The scheme can be employed in a privacy protected surveillance system, whereby visual objects are encrypted so that the content is only available to authorized personnel with the correct decryption key. The secure visual object coder employs shape and texture set partitioning in hierarchical trees (ST-SPIHT) along with a novel selective encryption scheme for efficient, secure storage and transmission of visual object shape and textures. The encryption is performed in the compressed domain and does not affect the rate-distortion performance of the coder. A separate parameter for each encrypted object controls the strength of the encryption versus required processing overhead. Security analyses are provided, demonstrating the confidentiality of both the encrypted and unencrypted portions of the secured output bit-stream, effectively securing the entire object shape and texture content. Experimental results showed that no object details are revealed to attackers who do not possess the correct decryption key. Using typical parameter values and output bit-rates, the SecST-SPIHT coder is shown to require encryption on less than 5% of the output bit-stream, a significant reduction in computational overhead compared to "whole content" encryption schemes.
An encoder architecture that employs view warping and sparse prediction (WaSP) has recently been proposed by the JPEG Pleno standards activity for the compression of light field imagery. The proposed WaSP encoder util...
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ISBN:
(纸本)9781538662496
An encoder architecture that employs view warping and sparse prediction (WaSP) has recently been proposed by the JPEG Pleno standards activity for the compression of light field imagery. The proposed WaSP encoder utilises disparity information to exploit the correlation that exists between multiple views and therefore requires disparity data to be communicated. The WaSP framework currently employs JPEG2000 for the coding of disparity maps. In this work we explore the impact of introducing breakpoint adaptive DWT (BPA-DWT) coding of disparity maps. While prior work has shown promising results for the coding of depth maps with breakpoints, its impact on multi-view compression where the depth or disparity data forms part of the communicated side information has not been previously explored. Our investigations show important gains in RD performance coupled with improvements in the visual quality of decoded views by the introduction of BPA-DWT coding of disparity maps.
State-of-the-art video coding techniques employ block-based illumination compensation to improve coding efficiency. In this work, we propose a Lifting-based Illumination Adaptive Transform (LIAT) to exploit temporal r...
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ISBN:
(纸本)9781509021758
State-of-the-art video coding techniques employ block-based illumination compensation to improve coding efficiency. In this work, we propose a Lifting-based Illumination Adaptive Transform (LIAT) to exploit temporal redundancy among frames that have illumination variations, such as the frames of low frame rate video or multi-view video. LIAT employs a mesh-based spatially affine model to represent illumination variations between two frames. In LIAT, transformed frames are jointly compressed, together with illumination information, into a layered rate-distortion optimal codestream, using the JPEG2000 format. We show that the LIAT framework significantly improves compression efficiency of temporal sub band transforms for both predictive and more general transforms with predict and update steps.
In this paper, we propose a compression scheme that is tailored for stereo-laparoscope sequences. The inter-frame correlation is modeled by the deformation field obtained by elastic registration between. two subsequen...
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ISBN:
(纸本)9780819466303
In this paper, we propose a compression scheme that is tailored for stereo-laparoscope sequences. The inter-frame correlation is modeled by the deformation field obtained by elastic registration between. two subsequent frames and exploited for prediction of the left sequence. The right sequence is lossy encoded by prediction from the corresponding left images. wavelet-based coding is applied to both the deformation vector fields and residual images. The resulting system supports spatio temporal scalability, while providing lossless performance. The implementation of the wavelet transform by integer lifting ensures a low computational complexity, thus reducing the required run-time memory allocation and on line implementation. Extensive psychovisual tests were performed for system validation and characterization with respect to the MPEG4 standard for video coding. Results are very encouraging: the PSVC system features the functionalities making,it suitable for PACS while providing a good trade-off between usability and performance in lossy mode.
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