When processing a signal or an image using the Discrete Cosine Transform (DCT) or Discrete Sine Transform (DST), a typical approach is to extract a portion of the signal by windowing and then form the DCT or DST of th...
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ISBN:
(纸本)0819457949
When processing a signal or an image using the Discrete Cosine Transform (DCT) or Discrete Sine Transform (DST), a typical approach is to extract a portion of the signal by windowing and then form the DCT or DST of the window contents. By shifting the window point by point over the signal, the entire signal may be processed. DCTs and DSTs are defined where the denominator in the transform kernel is either an odd or an even integer, resulting in transforms known as the even DCT (EDCT), even DST (EDST), odd DCT (ODCT) and odd DST (ODST). Each is available in types I to IV, for a total of 16 different transforms. The widely used transform commonly called the "DCT" is actually the EDCTII. In this paper we extend our previous work using the EDCT-II and EDST-II, and show that a similar approach yields algorithms for the ODCT-II and ODST-II. We develop algorithms to "update" the ODCT-II and ODST-II simultaneously to reflect the modified window contents using less computation than directly evaluating the modified transform via standard Fast Transform algorithms. These algorithms are able to handle arbitrary step sizes up to the length of the transform, i.e. the algorithm simultaneously updates the ODCT-II and ODST-II to reflect inclusion of r, where 1 <= r <= N-1, additional data points and removal of r old points from the signal. Examples of applications where this algorithm would be useful include target recognition where time constraints may not permit the immediate processing of every incoming data point, adaptive system identification, etc.
We propose a novel video coding scheme requiring a simple encoder and a complex decoder where video frames are intra-coded periodically and frames in between successive intra-coded frames are coded efficiently using a...
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ISBN:
(纸本)0819456586
We propose a novel video coding scheme requiring a simple encoder and a complex decoder where video frames are intra-coded periodically and frames in between successive intra-coded frames are coded efficiently using a proposed irregular binning technique. We investigate a method of forming an irregular binning which is capable of quantizing any value effectively with only small number of bins, by exploiting the correlation between successive frames. This correlation is additionally exploited at the decoder, where the quality of reconstructed frames is enhanced, gradually by applying POCS (projection on the convex sets). After an image frame is reconstructed with the irregular binning information at the proposed decoder, we can further improve the resulting quality by modifying the reconstructed image with motion-compensated image components from the neighboring frames. In the proposed decoder, several iterations of these modification and re-projection steps can be invoked. Experimental results show that the performance of the proposed coding scheme is comparable to that of H.264/AVC coding in IB mode. Since the proposed video coding does not require motion estimation at the encoder, it can be considered as an alternative for some versions of H.264/AVC in applications requiring a simple encoder.
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 detection of edits in a video sequence is the first step in video analysis, which segments a video into its basic components. Spatio-temporal slice analysis is an effective method for video partitioning because it...
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ISBN:
(纸本)0819459763
The detection of edits in a video sequence is the first step in video analysis, which segments a video into its basic components. Spatio-temporal slice analysis is an effective method for video partitioning because it can detect and classify different scene breaks. In a spatio-temporal slice, cut and wipe can be detected successfully based on measuring the changes of the color-texture properties of the slices. Dissolve can be measured by means of the parabolic variance curve (PVC) method. However, the statistical information extracted from the horizontal, vertical, and diagonal slices is not enough to show the PVC features. Thus, Support Vector Machine (SVM)-based dissolve detector was proposed, which extracts features based on the Gabor wavelets from a spatio-temporal slice and then identifies dissolves by means of the SVM-based classifier. However, this method is computationally intensive. In our method, we propose an efficient dissolve detector based on the spatio-temporal slices by using three simple second-order filters. Based on the linear estimation of the successive frames in a video shot, dissolve and static scenes exhibit different patterns in the temporal dimension. By applying the three simple filters, we can identify dissolves with arbitrary lengths accurately. Experiments based on the MPEG-7 standard sequences show encouraging results.
Remote sensing data products need to meet stringent geodetic and geometric accuracy specifications irrespective of intended user applications. Georeferencing is the basic processing step towards achieving this goal. H...
Remote sensing data products need to meet stringent geodetic and geometric accuracy specifications irrespective of intended user applications. Georeferencing is the basic processing step towards achieving this goal. Having known the imaging geometry and mechanism, the mathematical models built with the use of orbit and attitude information of the spacecraft can correct the remote sensing data for its geometric degradations only up to system level accuracy (IRS-P6 DP Team, 2000). The uncertainties in the orbit and attitude information will not allow the geometric correction model to generate products of accuracy that can meet user requirements unless Ground Control Points (GCP) are used as reference geo-location landmarks. IRS-P6 data processing team has been entrusted with developing a software system to generate data products that will have desired geodetic and geometric accuracies with known limitations. The intended software system is called the Value Added Data Products System (VADS). Precision corrected, Template Registered, Merged and Ortho Rectified products are the value added products planned with VADS.
Advances in spectral imaging instrumentation during the last two decades has lead to higher image fidelity, tighter spatial resolution, narrower spectral resolution, and improved signal to noise ratios. An important s...
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ISBN:
(纸本)0819456683
Advances in spectral imaging instrumentation during the last two decades has lead to higher image fidelity, tighter spatial resolution, narrower spectral resolution, and improved signal to noise ratios. An important sub-classification of spectral imaging is chemical imaging, in which the sought-after information from the sample is its chemical composition. Consequently, chemical imaging can be thought of as a two-step process, spectral image acquisition and the subsequent processing of the spectral image data to generate chemically relevant image contrast. While chemical imaging systems that provide turnkey data acquisition are increasingly widespread, better strategies to analyze the vast datasets they produce are needed. The Generation of chemically relevant image contrast from spectral image data requires multivariate processing algorithms that can categorize spectra according to shape. Conventional chemometric techniques like inverse least squares, classical least squares, multiple linear regression, principle component regression, and multivariate curve resolution are effective for predicting the chemical composition of samples having known constituents, but are less effective when a priori information about the sample is unavailable. To address these problems, we have developed a fully automated non-parametric technique called spectral identity mapping (SIMS) that reduces the dependence of spectral image analysis on training datasets. The qualitative SIMS method provides enhanced spectral shape specificity and improved chemical image contrast. We present SIMS results of infrared spectral image data acquired from polymer coated paper substrates used in the manufacture of pressure sensitive adhesive tapes. In addition, we compare the SIMS results to results from spectral angle mapping (SAM) and cosine correlation analysis (CCA), two closely related techniques.
Video security is becoming more and more important today, as the number of installed cameras can attest. There are many challenging commercial applications to monitor people or vehicle traffic. The work reported here ...
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Video security is becoming more and more important today, as the number of installed cameras can attest. There are many challenging commercial applications to monitor people or vehicle traffic. The work reported here has both research and commercial motivations. Our goals are first to obtain an efficient intelligent system that can meet strong industrial surveillance system requirements and therefore be real-time, distributed. generic and robust, Our Second goal is to have g a development platform that allows researchers to conceive and easily test new vision algorithms thanks to its modularity and easy set-up. This paper focuses oil the image analysis modules. It considers the different kind of inputs, algorithm models in addition to delay and the need of generality.
The irradiance measurement performed by vision cameras is not noise-free due to both processing errors during CCD fabrication and the behaviour of the electronic device itself. A proper characterization of sensor perf...
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ISBN:
(纸本)354029032X
The irradiance measurement performed by vision cameras is not noise-free due to both processing errors during CCD fabrication and the behaviour of the electronic device itself. A proper characterization of sensor performance, however, allows accounting for it within imageprocessing algorithms. This paper proposes a robust algorithm named (RCIU)-C-2 for characterizing the noise sources affecting CCD performance with the aim of estimating the uncertainty of the intensity values yielded by vision cameras. Experimental results can be found at the end of the paper.
Technological advances in digital imaging and liquid crystal tunable filters allow for a design of a both compact and cost effective multispectral camera system. Thus an image acquisition system for the visible and ne...
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Technological advances in digital imaging and liquid crystal tunable filters allow for a design of a both compact and cost effective multispectral camera system. Thus an image acquisition system for the visible and near infrared wavelength range can be realised consisting of conventional CCD cameras and tunable filters whose spectral transmittace is controlled electronically. Due to their limited internal payload the use of a lightweight, compact camera system is of particular importance for applications involving mini-unmanned-aerial-vehicles (mini-UAVs). Within the scope of this paper a both compact and economical data acquisition system for multispecral images is described. Despite of their limited functionality (e.g. regarding calibration) in comparison with commercial systems such as AVIRIS the use of these upcoming compact multispectral camera systems can be advantageous in many applications. In order to maintain the systems low weight and price this work proposes to separate data acquisition and processing modules, and transmit pre-processed camera data online to a stationary high performance computer for further processing. Special focus is laid upon transmission paths with limited bandwidth.
Quadrature filters(5) are a well known means for local spectral analysis of images and to extract relevant structure. Recently(9), there has been the discovering of an isotropic quadrature filter for images that does ...
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ISBN:
(纸本)0819459763
Quadrature filters(5) are a well known means for local spectral analysis of images and to extract relevant structure. Recently(9), there has been the discovering of an isotropic quadrature filter for images that does not need steering with respect to orientation and provides the user with geometric (local orientation) and structural (local phase) information. Here, we present a further extension of this, an isotropic quadrature filter for 3D data. With only four convolutions we can calculate the local orientation, energy and the phase of locally intrinsically ID structures dagger in 3D image data. There is a wide variety of useful applications for a filter of this kind. In this paper, we will restrict ourselves to the application of phase-based motion or flow field estimation.
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