Ultrasound images provide the clinician with noninvasive, low cost, and real-time images that can help them in diagnosis, plannnig and therapy. However, although the human eye is able to derive the meaningful informat...
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ISBN:
(纸本)0769523722
Ultrasound images provide the clinician with noninvasive, low cost, and real-time images that can help them in diagnosis, plannnig and therapy. However, although the human eye is able to derive the meaningful information from these images, automatic processing.is very difficult because of the noise and artefacts present in the image. In this work, we propose to extend the current anisotropic diffusion technique to deal with the speckle noise present in the Ultrasound images. To this end, we use a previously derived model of the noise, and we write the restoration scheme as a energy minization constrained by the noise model and parameters. This approach leads to a new data attachment term whose optimal weight can be automatically estimated.
In this paper, we have proposed a novel framework to achieve more effective classifier training by using unlabeled samples. By integrating concept hierarchy for semantic image concept organization, a hierarchical mixt...
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ISBN:
(纸本)0769523722
In this paper, we have proposed a novel framework to achieve more effective classifier training by using unlabeled samples. By integrating concept hierarchy for semantic image concept organization, a hierarchical mixture model is proposed to enable multi-level image concept modeling and hierarchical classifier training. To effectively learn the base-level classifiers for the atomic image concepts at the first level of the concept hierarchy, we have proposed a novel adaptive EM algorithm to achieve more effective classifier training with higher prediction accuracy. To effectively learn the classifiers for the higher-level semantic image concepts, we have also proposed a novel technique for classifier combining by using hierarchical mixture model. The experimental results on two large-scale image databases are also provided.
We introduce a new method that characterizes typical local image features (e.g., SIFT [9], phase feature [3]) in terms of their distinctiveness, detectability, and robustness to image deformations. This is useful for ...
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ISBN:
(纸本)0769523722
We introduce a new method that characterizes typical local image features (e.g., SIFT [9], phase feature [3]) in terms of their distinctiveness, detectability, and robustness to image deformations. This is useful for the task of classifying local image features in terms of those three properties. The importance of this classification process for a recognition system using local features is as follows: a) reduce the recognition time due to a smaller number of features present in the test image and in the database of model features;b) improve the recognition accuracy since only the most useful features for the recognition task are kept in the model database;and c) increase the scalability of the recognition system given the smaller number of features per model. A discriminant classifier is trained to select well behaved feature points. A regression network is then trained to provide quantitative models of the detection distributions for each selected feature point. It is important to note that both the classifier and the regression network use image data alone as their input. Experimental results show that the use of these trained networks not only improves the performance of our recognition system, but it also significantly reduces the computation time for the recognition process.
Most existing methods of reflection components decomposition using a single color image require color segmentation. Few methods that employ local operations are able to avoid the requirement;however, they usually suff...
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This paper presents a technique to learn dynamic appearance models from a small number of training frames. Under this framework, dynamic appearance is modelled as an unknown operator that satisfies certain interpolati...
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We address the tone reproduction problem by integrating local adaptation with global-contrast consistency. Many previous works have tried to compress high-dynamic-range (HDR) luminances into a displayable range in imi...
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ISBN:
(纸本)0769523722
We address the tone reproduction problem by integrating local adaptation with global-contrast consistency. Many previous works have tried to compress high-dynamic-range (HDR) luminances into a displayable range in imitation of the local adaptation mechanism of human eyes. Nevertheless, while the realization of local adaptation is not theoretically defined, exaggerating such effects often causes unnatural global contrasts. We propose a luminance-driven perceptual grouping process to derive a sparse representation of HDR luminances, and use the grouped regions to approximate local properties of luminances. The advantage of incorporating a sparse representation is twofold: We can simulate local adaptation based on region information, and subsequently apply piecewise tone mappings to monotonize the relative brightness over only a few perceptually significant regions. Our experimental results show that the proposed framework gives a good balance in preserving local details and maintaining global contrasts of HDR scenes.
Reconfigurable hardware, in the form of Field Programmable Gate Arrays (FPGAs), is becoming increasingly attractive for digital signal processing.problems, including imageprocessing.and computer vision tasks. The abi...
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In this demonstration, we present the Automatic Linguistic Indexing of Pictures (ALIP) system. The system annotates images with linguistic terms, chosen among hundreds of such terms. The system uses a wavelet-based ap...
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ISBN:
(纸本)0769523722
In this demonstration, we present the Automatic Linguistic Indexing of Pictures (ALIP) system. The system annotates images with linguistic terms, chosen among hundreds of such terms. The system uses a wavelet-based approach for feature extraction, a statistical modeling process for training, and a statistical significance processor to annotate images. We implemented and tested our ALIP system on a photographic image database of 600 different concepts, each with about 40 training images. The ALIP system has been used to annotate about 60,000 photographic images. In this demonstration, we illustrate the algorithms in the system and show the annotation results. With distributed computation, the annotation of an image can be provided in real-time. The demonstration system is available online at the site http://***.-***.
We report on four algorithms for recovering dense depth maps from long image sequences, where the camera motion is known a priori. All methods use a Kalman filter to integrate intensity derivatives or optical flow ove...
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We introduce a behavior-based similarity measure which tells us whether two different space-time intensity patterns of two different video segments could have resulted from a similar underlying motion field. This is d...
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ISBN:
(纸本)0769523722
We introduce a behavior-based similarity measure which tells us whether two different space-time intensity patterns of two different video segments could have resulted from a similar underlying motion field. This is done directly from the intensity information, without explicitly computing the underlying motions. Such a measure allows us to detect similarity between video segments of differently dressed people performing the same type of activity. It requires no foreground/background segmentation, no prior learning of activities, and no motion estimation or tracking. Using this behavior-based similarity measure, we extend the notion of 2-dimensional image correlation into the 3dimensional space-time volume, thus allowing to correlate dynamic behaviors and actions. Small space-time video segments (small video clips) are "correlated" against entire video sequences in all three dimensions (x,y, and t). Peak correlation values correspond to video locations with similar dynamic behaviors. Our approach can detect very complex behaviors in video sequences (e.g., ballet movements, pool dives, running water), even when multiple complex activities occur simultaneously within the field-of-view of the camera.
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