A Support Vector Machine (SVM) with the auto-correlation of compactly supported wavelet as kernel is proposed in this paper. It is proved that this kernel is an admissible support vector kernel. The main advantage of ...
详细信息
ISBN:
(纸本)0769523196
A Support Vector Machine (SVM) with the auto-correlation of compactly supported wavelet as kernel is proposed in this paper. It is proved that this kernel is an admissible support vector kernel. The main advantage of the auto-correlation of a compactly supported wavelet is that it satisfies the translation invariant property, which is very important for signalprocessing. Also, we can choose a better wavelet from different choices of wavelet families for our auto- correlation wavelet kernel. Experiments on signal regression show that this method is better than the existing SVM function regression with the scalar wavelet kernel, the Gaussian kernel, and the exponential radial basis function kernel. It can be easily extended to other applications such as pattern recognition by using this newly developed auto- correlation wavelet SVM.
This paper describes a new color image segmentation method based on low-level features including color and texture. The mean-shift algorithm with color and spatial information in color image segmentation is in general...
详细信息
A novel method to detect smoke and/or flame by processing the video data generated by an ordinary camera monitoring a scene is proposed. It is assumed the camera is stationary. Since the smoke is semi-transparent, edg...
详细信息
Through analyzing the characteristic of wavelet coefficients' Shannon entropy of the remote sensing signal and that of white noise at different scales, a new method for estimating remote sensing signal from added ...
详细信息
Through analyzing the characteristic of wavelet coefficients' Shannon entropy of the remote sensing signal and that of white noise at different scales, a new method for estimating remote sensing signal from added white noise is proposed with the proportion of wavelet coefficients' Shannon entropy. The simulation results demonstrate that this method is simple, reliable, effective and feasible.
Discrete wavelet transform (DWT) became a powerful method for signalprocessing in the last decade. One of the most important applications of this tool is compression, for the bi-dimensional signals JPEG 2000 being an...
详细信息
ISBN:
(纸本)142440049X
Discrete wavelet transform (DWT) became a powerful method for signalprocessing in the last decade. One of the most important applications of this tool is compression, for the bi-dimensional signals JPEG 2000 being an example. Although the new standard offers better results than the old one, new innovating ideas can improve even the JPEG 2000. One idea is to use complex wavelet transforms, transforms that offers more directions, instead of classical DWT. This paper comes to show the superiority of complex wavelet transforms in image compression, testing a new transform developed by N.G. Mngsbury. For this, the Embedded Zero-Tree wavelet (EZW) algorithm proposed by Shapiro was used to compress images at some different bit rates.
This paper introduces the Interlevel Product (ILP) which is a transform based upon the Dual-Tree Complex wavelet. Coefficients of the ILP have complex values whose magnitudes indicate the amplitude of multilevel featu...
详细信息
ISBN:
(纸本)0780391349
This paper introduces the Interlevel Product (ILP) which is a transform based upon the Dual-Tree Complex wavelet. Coefficients of the ILP have complex values whose magnitudes indicate the amplitude of multilevel features, and whose phases indicate the nature of these features (e.g. ridges vs. edges). In particular, the phases of ILP coefficients are approximately invariant to small shifts in the original images. We accordingly introduce this transform as a solution to coarse scale template matching, where alignment concerns between decimation of a target and decimation of a larger search image can be mitigated, and computational efficiency can be maintained. Furthermore, template matching with ILP coefficients can provide several intuitive "near-matches" that may be of interest in image retrieval applications.
The aim of this paper is to discuss the important features of wavelet transform and other existing methods in compression of fingerprints. image quality is measured objectively using peak signal-to-noise ratio (PSNR)....
详细信息
Magnetic resonance (MR) images acquired with a high temporal resolution or high spatial resolution are usually with a penalty of low signal to noise ratio (SNR). It is necessary to remove the noise artifacts with impo...
详细信息
ISBN:
(纸本)0819457213
Magnetic resonance (MR) images acquired with a high temporal resolution or high spatial resolution are usually with a penalty of low signal to noise ratio (SNR). It is necessary to remove the noise artifacts with important image features such as edges preserved. hi this paper, we propose to use the improved wavelet-based multiscale anisotropic diffusion algorithm for MR imaging. Experimental results demonstrate that this denoising algorithm can significantly improve the SNR for MR images while preserving edges with good visual quality. The denoising results indicate that in MR imaging applications, we can almost doubly improve the temporal resolution or improve the spatial resolution while achieving high SNR and acceptable image quality.
In this work, a new model that combines the concepts of wavelet transformation and independent component analysis (ICA) is developed for the purpose of defect detection in textile images. In previous works, it has bee...
详细信息
image segmentation is one of the primary steps in image analysis. The purpose of segmentation is to partition the image into homogeneous regions. Features are of major importance in image segmentation. Features are us...
详细信息
暂无评论