In this paper, we present a novel approach on image object removal by extending subpatch texture synthesis technique into redundant wavelet transform (RDWT) domain. As an overcompleted wavelet transform, RDWT is shift...
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ISBN:
(纸本)9780819474957
In this paper, we present a novel approach on image object removal by extending subpatch texture synthesis technique into redundant wavelet transform (RDWT) domain. As an overcompleted wavelet transform, RDWT is shift invariant and obtained without downsampling. Also, each RDWT highpass subband exhibits one specific orientation features of the image, in horizontal, vertical, or diagonal. All these make RDWT ideal for performing texture synthesis object removal techniques. In our experiments, subpatch texture synthesis in RDWT is introduced to remove unwanted objects from digital photographs. Specifically, for each RDWT subband, depending on the subband orientation, a particular direction subpatch texture synthesis is applied independently. Experimental results reveal that our simple algorithm performs better than previous methods.
imageprocessing is usually associated with pattern recognition and is rather treated as a subject outside of the computer graphics interest. Basically computer graphics algorithms are used for the visualization of sc...
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imageprocessing is usually associated with pattern recognition and is rather treated as a subject outside of the computer graphics interest. Basically computer graphics algorithms are used for the visualization of scenes or models described using some abstract notation, while imageprocessing is used on the opposite way -i.e. when finding an abstract description of an analyzed pattern. This paper proposes to use the imageprocessing approach for rendering optical effects in computer graphics algorithms. Proposed algorithms can be used for the generation of realistic and artistic optical effects in real-time, in, for example, visual simulators, virtual reality or multi-media applications. (C) 1997 Elsevier Science B.V.
We propose fast algorithms for computing Discrete Sine and Discrete Cosine Transforms (DCT and DST) of types VI and vii. Particular attention is paid to derivation of fast algorithms for computing DST-vii of lengths 4...
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ISBN:
(纸本)9780819487452
We propose fast algorithms for computing Discrete Sine and Discrete Cosine Transforms (DCT and DST) of types VI and vii. Particular attention is paid to derivation of fast algorithms for computing DST-vii of lengths 4 and 8, which are currently under consideration for inclusion in ISO/IEC/ITU-T High Efficiency Video Coding (HEVC) standard.
Based on our research in the last 17 years (with 68 papers published) on the subject of artificial neural network studied from the point of view of N-dimension geometry, a novel neural network system, the dynamic neur...
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ISBN:
(纸本)9780819474957
Based on our research in the last 17 years (with 68 papers published) on the subject of artificial neural network studied from the point of view of N-dimension geometry, a novel neural network system, the dynamic neural network, is proposed here for detecting an unknown moving (or time-varying) object such that the object will not only be detected by its static images, but also by the way it moves if this object follows a constant moving pattern. The system is designed to identify the unknown object by comparing a few time-separated snapshots of the object to a few standard moving objects learned or memorized in the system. The identification is determined by a user entered accuracy control. It could be very accurate, yet still be quite robust and quite fast in identification (e. g., identification in real-time) because of the simplicity of the algorithm. It is different from most other neural network systems because it employs the ND geometrical concept.
Many imageprocessing operations can be abstracted into matrix operations. With the help of matrix analysis, we can understand the inherent properties of the operations and thus design better algorithms. In this paper...
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Many imageprocessing operations can be abstracted into matrix operations. With the help of matrix analysis, we can understand the inherent properties of the operations and thus design better algorithms. In this paper, we propose a matrix decomposition method referred to as identity-plus-row decomposition, The decomposition is particularly useful in design of parallel projection algorithms on mesh-connected computers. Projection is a frequently used process in imageprocessing and visualization. In volume graphics, projection is used to render the essential content of a three-dimensional volume onto a two-dimensional image plane. For Radon transform, projection is used to transform the image space into a parameter space. By applying the identity-plus-row matrix decomposition method, we solve the data redistribution problem due to the irregular data access patterns present in those applications on single instruction stream, multiple data stream (SIMD) mesh-connected computers, developing fast algorithms for volume rendering and Radon transform on SIMD mesh-connected computers. (C) 2001 SPIE and IS&T.
The total variational (TV) regularization method was first proposed in(14) for gray scale images and was extended in(1) for vector valued images. In this work, we apply the TV regularization method to solve the multic...
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ISBN:
(纸本)0819425842
The total variational (TV) regularization method was first proposed in(14) for gray scale images and was extended in(1) for vector valued images. In this work, we apply the TV regularization method to solve the multichannel image deconvolution problem. The motivation for regularizing with the TV norm is that it is extremely effective for recovering edges of images. In this paper, a fast iterative method is developed to solve the deconvolution problem. Our method involves solving linear systems and the conjugate gradient method is applied in which Fourier transform type preconditioners are used to speed up the convergence rate. Numerical experiments will demonstrate the effectiveness of the TV regularization method. In this paper, we will present some preliminary results on multichannel blind deconvolution with TV regularization.
The primary application considered in this paper is target detection in infra-red (IR) imagery for ground surveillance application. The problem is characterized by the need to rapidly search large areas, and ascertain...
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ISBN:
(纸本)0819457817
The primary application considered in this paper is target detection in infra-red (IR) imagery for ground surveillance application. The problem is characterized by the need to rapidly search large areas, and ascertain the presence and location of threat objects. The challenge is in not only processing large images rapidly, but also reducing false alarm rates while achieving high levels of correct target detections. Performance is a function of many factors including the clutter type and density, the quality of the image and target signature, and the adequacy of the target data base. Although many types of target detection algorithms exist, we use a method based on quadratic correlation filters. The results of independent tests and evaluations by Night Vision Laboratory are also presented.
This paper presents an analytical performance prediction model and methodology that can be used to predict the execution time, speedup, scalability and similar performance metrics of a targe set of imageprocessing op...
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This paper presents an analytical performance prediction model and methodology that can be used to predict the execution time, speedup, scalability and similar performance metrics of a targe set of imageprocessing operations running on a p-processor parallel system. The model which requires only a few parameters obtainable on a minimal system can help in the systematic design, evaluation and performance tuning of parallel imageprocessingsystems. Using the model one can reason about the performance of a parallel imageprocessing system prior to implementation. The method can also support programmers in detecting critical parts of an implementation and system designers in predicting hardware performance and the effect of hardware parameter changes on performance. The execution of parallel imageprocessing operations was studied and operations were arranged in three main problem classes based on data locality and the communication patterns of the algorithms. The core of the method is the derivation of the overhead function, as it is the overhead that determines the achievable speedup. The overheads were examined and modelled for each class. The use of the method is illustrated by four class-representative imageprocessingalgorithms: image-scalar addition, convolution, histogram calculation and the Fast Fourier Transform. The developed performance model has been validated on a 16-node parallel machine and it has been shown that the model is able to predict the parallel run-time and other performance metrics of parallel imageprocessing operations accurately.
In recent decades, hyperspectral images (HSI) have been widely exploited in many fields for rich information containing in them. Many algorithms have been brought out for endmember extracting, among which, VCA algorit...
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ISBN:
(纸本)9780819481320
In recent decades, hyperspectral images (HSI) have been widely exploited in many fields for rich information containing in them. Many algorithms have been brought out for endmember extracting, among which, VCA algorithm performs a better precision and lower complexity. However, endmembers of the same HIS extracted with traditional VCA algorithm are not always the same in different runs. After deeply analyzing, the authors have proposed an improved VCA algorithm to resolve that shortcoming. For verification, experiment and comparative study have been performed. On conclusion, the improved VCA algorithm has manifested higher efficiency and accuracy than the traditional one.
This paper describes a set of image segmentation algorithms for mineral froth images, based on gray-value valley detection and a kind of image classification. The size, shape, texture and color of froth bubbles are ve...
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This paper describes a set of image segmentation algorithms for mineral froth images, based on gray-value valley detection and a kind of image classification. The size, shape, texture and color of froth bubbles are very important pieces of information for production optimization in mineral processing. In order to determine these parameters, bubbles in a froth image first have to be delineated. Froth images display a large variation of image patterns and quality, thus it is difficult to use only a single algorithm for segmenting all images. To achieve successful segmentation the images are first classified into image classes. Then sets of segmentation algorithms are used, based on the different image classes. The segmentation algorithms and classification algorithms have been tested in a laboratory and in industrial on-line systems for froth images, the test results show that they are robust for froth images. The processing speed for the segmentation algorithm is much faster than for a standard morphological segmentation algorithm. The processing accuracy is comparable to manual drawn result. This test shows that the algorithms work satisfactorily. (C) 2003 Elsevier Ltd. All rights reserved.
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