George H. Freeman

Shape retrieval using triangle-area representation and dynamic space warping

In this paper, we present a shape retrieval method using triangle-area representation for nonrigid shapes with closed contours. The representation utilizes the areas of the triangles formed by the boundary points to measure the convexity/concavity of each point at different scales (or triangle side lengths). This representation is effective in capturing both local and global characteristics of a shape, invariant to translation, rotation, and scaling, and robust against noise and moderate amounts of occlusion. In the matching stage, a dynamic space warping (DSW) algorithm is employed to search efficiently for the optimal (least cost) correspondence between the points of two shapes. Then, a distance is derived based on the optimal correspondence. The performance of our method is demonstrated using four standard tests on two well-known shape databases. The results show the superiority of our method over other recent methods in the literature.

Geometry-Based Image Retrieval in Binary Image Databases

In this paper, a geometry-based image retrieval system is developed for multiobject images. We model both shape and topology of image objects using a structured representation called curvature tree (CT). The hierarchy of the CT reflects the inclusion relationships between the image objects. To facilitate shape-based matching, triangle-area representation (TAR) of each object is stored at the corresponding node in the CT. The similarity between two multiobject images is measured based on the maximum similarity subtree isomorphism (MSSI) between their CTs. For this purpose, we adopt a recursive algorithm to solve the MSSI problem and a very effective dynamic programming algorithm to measure the similarity between the attributed nodes. Our matching scheme agrees with many recent findings in psychology about the human perception of multiobject images. Experiments on a database of 13,500 real and synthesized medical images and the MPEG-7 CE-1 database of 1,400 shape images have shown the effectiveness of the proposed method.

Fractal image denoising

Over the past decade, there has been significant interest in fractal coding for the purpose of image compression. However, applications of fractal-based coding to other aspects of image processing have received little attention. We propose a fractal-based method to enhance and restore a noisy image. If the noisy image is simply fractally coded, a significant amount of the noise is suppressed. However, one can go a step further and estimate the fractal code of the original noise-free image from that of the noisy image, based upon a knowledge (or estimate) of the variance of the noise, assumed to be zero-mean, stationary and Gaussian. The resulting fractal code yields a significantly enhanced and restored representation of the original noisy image. The enhancement is consistent with the human visual system where extra smoothing is performed in flat and low activity regions and a lower degree of smoothing is performed near high frequency components, e.g., edges, of the image. We find that, for significant noise variance (sigma > or = 20), the fractal-based scheme yields results that are generally better than those obtained by the Lee filter which uses a localized first order filtering process similar to fractal schemes. We also show that the Lee filter and the fractal method are closely related.

Prostate segmentation algorithm using dyadic wavelet transform and discrete dynamic contour

Knowing the location and the volume of the prostate is important for ultrasound-guided prostate brachytherapy, a commonly used prostate cancer treatment method. The prostate boundary must be segmented before a dose plan can be obtained. However, manual segmentation is arduous and time consuming. This paper introduces a semi-automatic segmentation algorithm based on the dyadic wavelet transform (DWT) and the discrete dynamic contour (DDC). A spline interpolation method is used to determine the initial contour based on four user-defined initial points. The DDC model then refines the initial contour based on the approximate coefficients and the wavelet coefficients generated using the DWT. The DDC model is executed under two settings. The coefficients used in these two settings are derived using smoothing functions with different sizes. A selection rule is used to choose the best contour based on the contours produced in these two settings. The accuracy of the final contour produced by the proposed algorithm is evaluated by comparing it with the manual contour outlined by an expert observer. A total of 114 2D TRUS images taken for six different patients scheduled for brachytherapy were segmented using the proposed algorithm. The average difference between the contour segmented using the proposed algorithm and the manually outlined contour is less than 3 pixels.

Fractal-wavelet image denoising revisited

The essence of fractal image denoising is to predict the fractal code of a noiseless image from its noisy observation. From the predicted fractal code, one can generate an estimate of the original image. We show how well fractal-wavelet denoising predicts parent wavelet subetres of the noiseless image. The performance of various fractal-wavelet denoising schemes (e.g., fixed partitioning, quadtree partitioning) is compared to that of some standard wavelet thresholding methods. We also examine the use of cycle spinning in fractal-based image denoising for the purpose enhancing the denoised estimates. Our experimental results show that these fractal-based image denoising methods are quite competitive with standard wavelet thresholding methods for image denoising. Finally, we compare the performance of the pixel- and wavelet-based fractal denoising schemes

Multi-object image retrieval based on shape and topology

We aim at developing a geometry-based retrieval system for multi-object images. We model both shape and topology of image objects including holes using a structured representation called curvature tree (CT); the hierarchy of the CT reflects the inclusion relationships between the objects and holes. To facilitate shape-based matching, triangle-area representation (TAR) of each object and hole is stored at the corresponding node in the CT. The similarity between two multi-object images is measured based on the maximum similarity subtree isomorphism (MSSI) between their CTs. For this purpose, we adapt a continuous optimization approach to solve the MSSI problem and a very effective dynamic programming algorithm to measure the similarity between the attributed nodes. Our matching scheme agrees with many recent findings in psychology about the human perception of multi-object images. Experiments on a database of 1500 logos and the MPEG-7 CE-1 database of 1400 shape images have shown the significance of the proposed method.

A realistic approach to the capacity of cellular CDMA systems

The effects of imperfect power control and soft handoff on the capacity of DS-CDMA cellular systems are investigated. In our analysis, the approach is to employ appropriate models for signals and network configuration and derive analytical results. For power control error, the received signals at the cell site are modeled differently and the fitness of models are argued. In the other part, soft handoff effect in reducing forward-link capacity is studied based on a simplified cell model. The result of this study questions the improvement of system capacity due to soft handoff.

Fractal-wavelet image denoising

We propose a simple yet effective fractal-wavelet scheme for edge-preserving smoothing of noisy images. Over the past decade, there has been significant interest in fractal coding for the purpose of image compression. Fractal-wavelet transforms were introduced in an effort to reduce the blockiness and computational complexity that are inherent in fractal image compression. Applications of fractal-based coding to other aspects of image processing, however, have received little attention. The authors proposed a simple yet effective fractal-based image denoising scheme that is applied in the spatial domain of the image. We extend the application of this fractal denoising scheme to the wavelet domain of the image. We find that when the wavelet transform of the noisy image is simply fractally coded, a significant amount of the noise is suppressed. However, one can go a step further and estimate the fractal code of the wavelet transform of the original noise-free image from that of the wavelet transform of the noisy image. The use of the quadtree partitioning scheme for the purpose of fractal-wavelet coding results in a significantly enhanced and restored representation of the original noisy image. The enhancement is consistent with the human visual system where extra smoothing is performed in flat and low activity regions and a lower degree of smoothing is performed near high frequency components, e.g. edges, of the image. The main advantage of the wavelet-based fractal denoising scheme over the standard fractal denoising scheme is that it is computationally less expensive.

A hybrid subband adaptive system for speech enhancement in diffuse noise fields

Performance of adaptive noise cancellation (ANC) degrades severely when uncorrelated noise components are present at the two inputs. Thus, practical background diffuse noises pose a serious problem for ANC systems. In this letter, we propose a new hybrid system that integrates subband adaptive filters (SAFs) and a Wiener filter. The hybrid system is implemented on an oversampled DFT filterbank that efficiently integrates the SAF and the Wiener filter components in the frequency-domain. Performance evaluation of the hybrid system in presence of diffuse noise interference shows that the proposed system is superior to both the Wiener filter and the SAF subsystems.

Modeling and resource allocation in wireless multimedia CDMA systems

To comply with future communications needs, it is desirable to provide multimedia services at wireless access points. In a wireless multimedia context, resource allocation is crucial because the channel quality varies with time and the network resources are scarce. We address the resource allocation problem in wireless multimedia CDMA (code division multiple access) systems. The objectives are: (1) to develop a wireless multimedia model based on CDMA to provide data rate and quality of service (QoS) on demand and to integrate various traffic types efficiently, and (2) to develop a mathematical programming problem to optimize resource allocation based on a wireless service providers perspective. In comparison with the previous work, the proposed multimedia model supports a wider range of applications and service qualities, and combines power control, rate allocation and base station assignment with controlled handoff switching and dropped calls in a multi-cell environment.