The emergence of digital multimedia and the proliferation of its use have raised major concerns about the protection of intellectual property. In response to these concerns, digital watermarks have emerged as a possib...
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The emergence of digital multimedia and the proliferation of its use have raised major concerns about the protection of intellectual property. In response to these concerns, digital watermarks have emerged as a possible solution for protecting the intellectual property of digital content. In this paper, we derive estimates of data-hiding capacity of balanced multiwavelet transforms. This class of transforms, relatively new, has useful properties for imageprocessingapplications as shown in this paper. Furthermore, we investigate the relevance of two closely related statistical models, developed for scalar wavelets, for modeling the statistics of balanced multiwavelet transform coefficients. Finally, we present performance results of a spread spectrum watermarking system that is based on this new transform.
Motion plays a fundamental role in coding and processing of video signals. Existing approaches of modeling video source are mostly based on explicitly estimating motion information from intensity values. Despite its c...
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Motion plays a fundamental role in coding and processing of video signals. Existing approaches of modeling video source are mostly based on explicitly estimating motion information from intensity values. Despite its conceptual simplicity, motion estimation (ME) is a long-standing open problem itself and accordingly the performance of a system operated on inaccurate motion information is unlikely to be optimal. In this paper, we present a novel approach of modeling video signals without explicit ME. Instead, motivated by a duality between edge contour of image and motion trajectory of video, we demonstrate that the spatio-temporal redundancy in video can be exploited by Least-Square(LS) based adaptive filtering techniques. We consider the application of such implicit motion models into the problem of error concealment or more generally known as video inpainting. Our experimental results have shown the excellent performance of the proposed LS-based error concealment techniques under a variety of information loss conditions.
An innovative Fourier Transform hyperspectral imagine, system based on reflective optics is currently being studied. It can record both spatial images and spectral information of a sample instantaneously. Substantial ...
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ISBN:
(纸本)0819455954
An innovative Fourier Transform hyperspectral imagine, system based on reflective optics is currently being studied. It can record both spatial images and spectral information of a sample instantaneously. Substantial properties of the sample can be elucidated from such images. Compared to classical Imaging Spectrometer using lenses and prisms, the significant characteristic of this system is that it only uses reflective mirrors and just one beam splitter. Such structure will help to largely avoid the limitation of spectral range and the refraction non-homogenize both of which affect the quality of imaging. Therefore, the noticeable advantages of this system are high signal-to-noise ratio, high spatial and spectral resolution, large spectral bandwidth, high throughput, non-chromatic aberration and very compact optical structure in which just one imaging system could applicable to a rather wide spectral bandwidth. This project includes both theoretical analysis and development of an experimental instrument. With the instrument, the images that contain one-dimensional spatial image and another dimensional interferogram are already collected. The data processing system could transform the interferogram of each scene to its spectral information. The typical experimental results are given in this paper.
A new algorithm and a novel architecture suitable for FPGA/ASIC implementation of a video scalar is presented in this paper. The scheme proposed here results in enormous savings of memory normally required, without co...
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A new algorithm and a novel architecture suitable for FPGA/ASIC implementation of a video scalar is presented in this paper. The scheme proposed here results in enormous savings of memory normally required, without compromising on the image quality. In the present work, SVGA compatible video sequence is scaled up to xGA format. The up scaling operation for a video sequence is carried out by scaling up the image input, followed by down scaling and filtering. The FPGA implementation of the proposed video-scaling algorithm is capable of processing high-resolution, color pictures of sizes of up to 1024 x 768 pixels at the real time video rate of 30 frames/s. The video scalar is capable of scaling down xGA format to SVGA format as well. The design has been realized by RTL compliant Verilog coding, and fits into a single chip with a gate count utilization of two million gates. For lower resolution pictures, the mapped device can be scaled down. The present FPGA implementation compares favorably with another ASIC implementation. Also, an MPEG-2 codec implementation is presented for use in applications, where the video scalar and codec may be used to reduce transmission bit rate. Transmission of high resolution pictures of xGA format and above, even after effecting compression, demand very high serial channel bandwidth requirement, far exceeding the prescribed maximum by MPEG-2 standards. This can be circumvented by down scaling and then effecting compression before transmission, trading off for a little image quality, as presented in this paper. (c) 2004 Elsevier B.V. All rights reserved.
The main accomplishment of sampled-data control theory in the last decade is that it successfully derives a digital (discrete-time) control law that makes the overall analog (continuous-time) performance optimal. The ...
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The main accomplishment of sampled-data control theory in the last decade is that it successfully derives a digital (discrete-time) control law that makes the overall analog (continuous-time) performance optimal. The same hybrid nature of designing a digital filter for analog signals is also prevalent in digital signalprocessing. A crucial observation is that the perfect band-limiting hypothesis can be inadequate for many practical situations. In practice, the original analog signals (sounds, images, etc.) are neither fully band-limited nor even close to be bandlimited in the current processing standards. This is the problem of interpolating high-frequency components, which in turn is that of recovering the intersample behavior. Sampled-data control theory provides an optimal platform for such problems. This paper provides a new problem formulation, design procedure, and various applications in sound processing/ compression and imageprocessing.
Contouring of the target and risk anatomy is one of the most time consuming procedures in radiotherapy planning (RTP). The main imaging modality used in RTP is the computer tomography (CT), where the application of au...
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ISBN:
(数字)9783540264316
ISBN:
(纸本)3540250522
Contouring of the target and risk anatomy is one of the most time consuming procedures in radiotherapy planning (RTP). The main imaging modality used in RTP is the computer tomography (CT), where the application of automated segmentation methods in certain treatment areas, such as head and neck, is difficult due to insufficient soft tissue contrast. Magnetic resonance imaging (MRI) generates images with better soft tissue contrast, and it is expected that MRI will be more extensively used in RTP. Owing to the image formation principles, the feature variability of MR data is much higher compared to CT. In this paper, we present an approach that combines a model-based segmentation method with the pattern classification framework to segment organs in MR images of the head and neck area. A validation study demonstrates that the proposed approach is feasible for the organs tested.
Texture classification has long been an important research topic in imageprocessing. Classification based on the wavelet transform has become very popular. wavelets are very effective in representing objects with iso...
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Texture classification has long been an important research topic in imageprocessing. Classification based on the wavelet transform has become very popular. wavelets are very effective in representing objects with isolated point singularities, but failed to represent line singularities. Recently, a ridgelet transform which deals effectively with line singularities in 2-D is introduced. It allows representing edges and other singularities along lines in a more efficient way. In this paper, the issue of texture classification based on a ridgelet transform has been analyzed. Features are derived from sub-bands of the ridgelet decomposition and are used for classification for a data set containing 20 texture images. Experimental results show that this approach allows to obtain a high degree of success in classification.
Principal components analysis (PCA) has been widely used in many applications, particularly, data compression. Independent component analysis (ICA) has been also developed for blind source separation along with many o...
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Principal components analysis (PCA) has been widely used in many applications, particularly, data compression. Independent component analysis (ICA) has been also developed for blind source separation along with many other applications such as channel equalization, speech processing. Recently, it has been shown that the ICA can be also used for hyperspectral data compression. This paper investigates these two transforms in hyperspectral data compression and further evaluates their strengths and weaknesses in applications of target detection, mixed pixel classification and abundance quantification. In order to take advantage of the strengths of both transform, a new transform, called mixed PCA/ICA transform is developed in this paper. The idea of the proposed mixed PCA/ICA transform is derived from the fact that it can integrate different levels of information captured by the PCA and ICA. In doing so, it combines m principal components (PCs) resulting from the PCA and n independent components (ICs) generated by the ICA to form a new set of (m+n) mixed components used for hyperspectral data compression. The resulting transform is referred to as mixed (m,n)-PCA/ICA transform. In order to determine the total number of components, p needed to be generated for the mixed (m,m)-PCA/ICA transform, a recently developed virtual dimensionality (VD) is introduced to estimate the p where p = m + n. If m = p and n = 0, then mixed (m,n)-PCA/ICA transform is reduced to PCA transform. On the other hand, if m = 0 and n = p, then mixed (m,n)-PCA/ICA transform is reduced to ICA. Since various combinations of m and n have different impacts on the performance of the mixed PCA/ICA spectral/spatial compression in applications, experiments based on subpixel detection and mixed pixel quantification are conducted for performance evaluation.
An algorithm for robust transmission of compressed 3-D mesh data is proposed in this work. In the encoder, we partition a 3-D mesh adaptively according to the surface complexity, and then encode each partition separat...
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ISBN:
(纸本)0819460397
An algorithm for robust transmission of compressed 3-D mesh data is proposed in this work. In the encoder, we partition a 3-D mesh adaptively according to the surface complexity, and then encode each partition separately to reduce the error propagation effect. To encode joint boundaries compactly, we propose a boundary edge collapse rule, which also enables the decoder to zip partitions seamlessly. In the decoder, an error concealment scheme is employed to improve the visual quality of corrupted partitions. The concealment algorithm utilizes the information in neighboring partitions and reconstructs the lost surface based on the semi-regular connectivity reconstruction and the polynomial interpolation. Simulation results demonstrate that the proposed algorithm provides a good rendering quality even in severe error conditions.
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