In this paper, a learnable cellular nonlinear network (CNN) with space-variant templates, ratio memory (RM), and modified Hebbian learning algorithm is proposed and analyzed. By integrating both the modified Hebbian l...
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In this paper, a learnable cellular nonlinear network (CNN) with space-variant templates, ratio memory (RM), and modified Hebbian learning algorithm is proposed and analyzed. By integrating both the modified Hebbian learning algorithm with the self-feedback function and a ratio memory into CNN architecture, the resultant ratio-memory (RMCNN) is called the self-feedback RMCNN (SRMCNN) which can serve as the associative memory. It can generate the absolute weights and then transform them into the ratioed A-template weights as the ratio memories for recognizing noisy input patterns. Simulation results have shown that with the stronger feature enhancement effect, the SRMCNN under constant leakage current can store and recognize more patterns than the RMCNN. For 18 x 18 SRMCNN, 93 noisy patterns with a uniform distribution noise level of 0.8 and a variance of normal distribution noise of 0.3 can be learned, stored, and recognized with 100% success rate. The SRMCNN has greater learning and recognition capability when the learned patterns are simpler and the noise is lower. For the learning and recognition of complicated patterns, the allowable pattern number is decreased for a 100% success rate. Simulation results have successfully verified the correct functions and better performance of SRMCNN in the pattern recognition. With high integration capability and excellent pattern association performance, the proposed SRMCNN can be applied to nanoelectronic associative-memory systems for imageprocessingapplications.
Lighting plays an important role in many applications of computer vision, machine vision and computer graphics. Often, an object needs to be photographed multiple times, in each of which lighting comes from a differen...
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ISBN:
(纸本)0819454672
Lighting plays an important role in many applications of computer vision, machine vision and computer graphics. Often, an object needs to be photographed multiple times, in each of which lighting comes from a different direction. Lighting which uses a single source per image is prone to dynamic range problems, especially in dark areas and in specular highlights. In addition, it becomes a practical problem to use an increasingly larger number of discrete sources (say, hundreds). To counter these problems we develop a novel illumination strategy. In each image, multiple light sources irradiate the scene simultaneously. The set of light sources is different in each image, but not mutually exclusive. Then, the contribution of each individual source is extracted in computational post-processing. The number of acquired images using this approach is the same as the number used in single-source images. However, thanks to the multiplexing of light in the raw images, more light is used from a variety of directions, diminishing problems of dynamic rang e. We derive the optimal illumination multiplexing scheme, which increases the SNR of the images by rootn/2. where n is the number of sources. This lighting strategy is complemented by a novel illumination setup. The setup is easily built and scaled to a huge number of sources, and is controllable by the computer. These advantages are obtained since the apparatus is based on indirect lighting originating from an LCD projector.
Spread-spectrum watermarking scheme adds random noise w into the host signalx to generate watermarked signal s. Blind detector computes inner product 〈w, s〉 or its variants (i.e., correlation) and decides if the host...
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Spread-spectrum watermarking scheme adds random noise w into the host signalx to generate watermarked signal s. Blind detector computes inner product 〈w, s〉 or its variants (i.e., correlation) and decides if the host signal contains embedded bits or not by its sign of the inner product. Such detection method may not be sufficiently robust in some applications due to high false-positive or false-negative rate. This paper introduces a novel method to reduce detection errors considerably by excluding outliers in the signal. First, this paper identifies the usefulness of the outliers. Second, this paper identifies the problem of outliers. Due to the vague definition of outlier, it was impossible to draw unique criterion for outlier. Thus, third, stable and robust definition of outlier is adopted. Informed watermarking scheme for spread-spectrum is exploited to reduce false-positive and false-negative errors. Such detectors can also enhance detection rate in other watermarking schemes. This scheme can enhance robustness of image watermarking and audio watermarking as well.
This paper presents results from investigations of mixing flowfields and optical gain profiles in HF chemical laser systems by infrared hyperspectral imaging. A chemiluminescent F + H-2 reacting flowfield, produced in...
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ISBN:
(纸本)0819452424
This paper presents results from investigations of mixing flowfields and optical gain profiles in HF chemical laser systems by infrared hyperspectral imaging. A chemiluminescent F + H-2 reacting flowfield, produced in a high-fluence microwave-driven reactor, was imaged at a series of wavelengths, 2.6 to 2.9 mum, by a low-order, spectrally scanning Fabry-Perot interferometer mated to an infrared camera. The resulting hyperspectral data cubes define the spectral and spatial distributions of the emission. High-resolution images were processed to determine spatial distributions of the excited state concentrations of the product HF(v,J), as well as spatial distributions of small-signal gain on specific laser transitions. Additional high-resolution Fourier transform spectroscopy and spectral fitting analysis determined detailed excited state distributions in the reacting flowfield. The measurements confirm that our reactor generates inverted populations of HF(v,J).
Thermoacoustic tomography (TAT) is an emerging imaging technique with great potential for a wide range of biomedical imaging applications. In this work, we propose and investigate reconstruction approaches for TAT tha...
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ISBN:
(纸本)0819452866
Thermoacoustic tomography (TAT) is an emerging imaging technique with great potential for a wide range of biomedical imaging applications. In this work, we propose and investigate reconstruction approaches for TAT that are based on the half-time reflectivity tomography paradigm. We demonstrate that half-time reconstruction approaches can produce images in TAT that possess better statistical properties than images produced by use of conventional reconstruction approaches.
image compression will always reduce the image fidelity, especially when the image is compressed at lower bit rates, which cannot be tolerated, especially in medical field. But compression is necessary due to the cons...
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image compression will always reduce the image fidelity, especially when the image is compressed at lower bit rates, which cannot be tolerated, especially in medical field. But compression is necessary due to the constraint of transmission bandwidth and the limited storage capacity. In this paper, the bad compression performance of the new JPEG2000 and the more conventional JPEG are studied. Besides, using the common objective measures such as Peak signal-to-Noise Ratio (PSNR) and Root Mean Square Error (RMSE) as the standard quality measurements, we focus more on the statistical and frequency measures as the image characteristics evaluation. Four types of medical modalities are used: x-ray, Magnetic Resonance Imaging (MRI), Ultrasound and Computed Tomography (CT). From these various measurements, we found the general acceptance compression bit rate for each of the medical modalities.
A novel technique for the secret video communicating based on the discrete wavelet transform(DWT) is present. Transform a intra frame of video to three gray image firstly, and then compute the Lth-level discrete wavel...
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ISBN:
(纸本)981238961X
A novel technique for the secret video communicating based on the discrete wavelet transform(DWT) is present. Transform a intra frame of video to three gray image firstly, and then compute the Lth-level discrete wavelet decomposition of the gray images, with which the secret data W is embed simultaneously and do invert wavelet transform to obtain the gray images which contains the secret information. Change the intra frame of video based the three gray images to make the intra frame contain the secret information. When extract the secret information, transform the intra frame to three gray image and do Lth-level discrete wavelet transform to the gray images, distill the secret data W' from the wavelet coefficients of the three gray images. Test results show the superior performance of the technique and potential for the secret communicating of video.
wavelets have been studied and applied in the multimedia and video processing community, including some areas in medical imaging, however, wavelet-based medical image registration has not been explored properly. In th...
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wavelets have been studied and applied in the multimedia and video processing community, including some areas in medical imaging, however, wavelet-based medical image registration has not been explored properly. In this paper, we propose an hierarchical registration method based on wavelet decomposition. Firstly, based on the wavelets, the images are decomposed into subbands which compose the registration pyramid; then, in each hierarchy, the affine registration based on mutual information is performed and the results of the current registration are used as the initial guess for the next hierarchy; finally, to further improve the registration performance, the local elastic registration is carried out. The proposed algorithm has been validated by experiments on clinical tomographic images and our experimental results demonstrate the the proposed method is of efficiency and good accuracy.
Reducing noise has always been one of the standard problems of the image anal- ysis and processing community. Whether motivated by itself or by some practical application such as preprocessing for e. g. medical image ...
Reducing noise has always been one of the standard problems of the image anal- ysis and processing community. Whether motivated by itself or by some practical application such as preprocessing for e. g. medical image segmentation, a multi- tude of methods have been proposed to remove noise. Some are useful, others are not as beneficial. This thesis presents a framework for denoising by first examin- ing what the problem really is. What is a signal What is noise What is to be removed A method based on Bayesian analysis is presented for denoising. The method is evaluated in theory and practise on artificial and real data and a num- ber of applications incorporating the proposed method are discussed. The field of medical image analysis is given special emphasis in the form of a chapter devoted purely to medical image denoising with example applications in MRI, ultrasound and digital x-ray imaging. The result is a method to reduce spatially uncorrelated noise in two- and three- dimensional images making explicit use of available knowledge on the noise statistics. The method uses very few and intuitive parameters. The parameters. are easy to choose either as standard values or by simple estimation schemes.
This paper presents the performance evaluation of a watermarking algorithm, an image and video processing technique used for Digital Right Management. Software developments are largely used in image copyright applicat...
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This paper presents the performance evaluation of a watermarking algorithm, an image and video processing technique used for Digital Right Management. Software developments are largely used in image copyright applications but there is a lack of real time applications for video. A previous work in image watermarking was already done and proposed a new algorithm with very interesting security properties. Nevertheless, the software implementation of this watermarking scheme showed some restrictions concerning real time applications. Hence, we propose to extend the previous paper with a lighter version of the algorithm and a complete hardware implementation allowing us to deal with high throughput image/video applications, such as digital cinema.
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