A flexible multiscale and directional representation for images is proposed. The scheme combines directional filter banks with the Laplacian pyramid to provide a sparse representation for two-dimensional piecewise smo...
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A flexible multiscale and directional representation for images is proposed. The scheme combines directional filter banks with the Laplacian pyramid to provide a sparse representation for two-dimensional piecewise smooth signals resembling images. The underlying expansion is a frame and can be designed to be a tight frame. Pyramidal directional filter banks provide an effective method to implement the digital curvelet transform. The regularity issue of the iterated filters in the directional filter bank is examined.
This paper describes a connected component (CC)-based approach to automatic text location and segmentation in natural scene images. A multi-group decomposition scheme is used to deal with the complexity of the color b...
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ISBN:
(纸本)076951183X
This paper describes a connected component (CC)-based approach to automatic text location and segmentation in natural scene images. A multi-group decomposition scheme is used to deal with the complexity of the color background. Connected component extraction is implemented using the block adjacency graph (BAG) algorithm after noise filtering and runlength smearing (RLS) operation. Some heuristic features and priority adaptive segmentation (PAS) of characters are proposed in block candidate verification and grayscale-based recognition. A prototype system is completed and the experimental results prove the effectiveness of the proposed method.
This paper proposes some modifications to reference models of the human visual system for the benefit of a best performing fingerprinting scheme inside wavelet decompressors. Two new algorithms have been developed, ba...
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This paper proposes some modifications to reference models of the human visual system for the benefit of a best performing fingerprinting scheme inside wavelet decompressors. Two new algorithms have been developed, based on more accurate modeling for luminance masking and on experimental tests for texture masking. In order to manifest the improvements, the insertion gain of the masks relative to non-perceptual watermarking schemes is calculated and compared to the one obtained by the reference technique. Also, the masks' energy distribution is checked to validate them as weighting functions of the watermark.
We introduce a selective encryption scheme for visual data based on the wavelet packet representation where the structure of a randomly chosen non-stationary multi-resolution analyses (NSMRA) is encrypted only. Wherea...
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We introduce a selective encryption scheme for visual data based on the wavelet packet representation where the structure of a randomly chosen non-stationary multi-resolution analyses (NSMRA) is encrypted only. Whereas the rate-distortion performance of the entire scheme is on an acceptable level we describe a heuristic to break the proposed scheme in linear time.
Various approaches based on Kalman filtering exist in the literature for image restoration. The reduced order model Kalman filter (ROMKF) has comparable performance with less computational complexity. For further redu...
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Various approaches based on Kalman filtering exist in the literature for image restoration. The reduced order model Kalman filter (ROMKF) has comparable performance with less computational complexity. For further reduction in computational complexity, we suggest a simplified model Kalman filter (SMKF) for image restoration. Furthermore, a hybrid approach based on discrete wavelet transform (DWT) and SMKF is proposed for image restoration with better SNRs especially when the observed image signal-to-noise ratio is low. In the first step, the approach uses the DWT with few resolution levels and a moderate threshold value for denoising the image. The denoised image will provide a better data to SMKF in the second step. The proposed approach is implemented on a visualimage to evaluate its performance in comparison with the SMKF and DWT approaches.
In ATM networks cell loss or channel errors can cause data to be dropped in the channel. When digital images/video are transmitted over these networks one must be able to reconstruct the missing data so that the impac...
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In ATM networks cell loss or channel errors can cause data to be dropped in the channel. When digital images/video are transmitted over these networks one must be able to reconstruct the missing data so that the impact of the errors is minimized. We overview the problem of using EZW encoders in channels where data-loss is possible. We also describe an error resilience scheme based on unequal error protection and data interleaving that addresses the problem of using rate scalable encoders over ATM networks.
Prefetching is a widely adopted technique for improving performance of cache memories. Performances are typically affected by the design parameters, such as cache size and associativity, but also by the type of locali...
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ISBN:
(纸本)0780370015
Prefetching is a widely adopted technique for improving performance of cache memories. Performances are typically affected by the design parameters, such as cache size and associativity, but also by the type of locality embodied in the programs. In particular multimedia tools and programs handling images and video are characterized by a bi-dimensional spatial locality that could be greatly exploited by the inclusion of prefetching in the cache architecture. In this paper we compare some prefetching techniques for multimedia programs (such as MPEG compression, imageprocessing, visual object segmentation) by performing a detailed evaluation of the memory access time. The goal is to prove that a significant speedup can be achieved by using either standard prefetching techniques (such as OBL or adaptive prefetching) or some innovative and image-oriented prefetching methods like the neighbor prefetching described in the paper. Performance are measured with the PRIMA trace-driven simulator.
A novel adaptive nonlinear filter is proposed aimed at smoothing homogenous regions while maintaining image structures. The filter can be utilized as a pre-processing tool in image segmentation and edge estimation for...
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A novel adaptive nonlinear filter is proposed aimed at smoothing homogenous regions while maintaining image structures. The filter can be utilized as a pre-processing tool in image segmentation and edge estimation for improving the results. Several special features are introduced to the filter, including using local adaptive radial clustering and pixel filtering to exclude the influence of outliers and to maintain image structures; using the steepest-ascent method to iteratively update pixels to the nearest clusters obtained by mean-shift; and introducing highly parallel processing by using random seed samples and their associated data blocks which enables fast processing and the global optimum solution of the nonlinear filter. Experiments were done on images of various complexities, and good results were obtained. Evaluations of the filter were also done in terms of edge preservation and image segmentation.
A new vector approach, the adaptive vector LUM smoother for color images is presented. The novelty of the proposed method lies in the two-stages adaptive choice of the estimate, where in the first filter stage (N+1)/2...
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A new vector approach, the adaptive vector LUM smoother for color images is presented. The novelty of the proposed method lies in the two-stages adaptive choice of the estimate, where in the first filter stage (N+1)/2 outputs with all smoothing levels done by the vector LUM smoother with window size N are generated. In the next filter stage, one of (N+1)/2 possible samples is adaptively selected to determine the filter output depending on the local information, by the filter window. Thus, the proposed method provides an optimal estimate in the sense of objective criteria. In addition, the filter output is constrained to be a sample from an input set that cannot result in color artifacts.
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