L. Irene Cheng

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A single captured image of a real-world scene is usually insufficient to reveal all the details due to under- or over-exposed regions. To solve this problem, images of the same scene can be first captured under different exposure settings and then combined into a single image using image fusion techniques. In this paper, we propose a novel probabilistic(More)
In this paper, we propose a new approach that we call the "fluid vector flow" (FVF) active contour model to address problems of insufficient capture range and poor convergence for concavities. With the ability to capture a large range and extract concave shapes, FVF demonstrates improvements over techniques like gradient vector flow, boundary vector flow,(More)
Tuberculosis (TB) is a deadly infectious disease and the presence of cavities in the upper lung zones is a strong indicator that the disease has developed into a highly infectious state. Currently, the detection of TB cavities is mainly conducted by clinicians observing chest radiographs. Diagnoses performed by radiologists are labor intensive and very(More)
Many factors, such as the number of vertices and the resolution of texture, can affect the display quality of 3D objects. When the resources of a graphics system are not sufficient to render the ideal image, degradation is inevitable. It is therefore important to study how individual factors will affect the overall quality, and how the degradation can be(More)
Multimedia data are now available to a variety of users ranging from naive to sophisticated. To make querying easy, visual query languages have been proposed. Most of these languages have a low expressive power and have their own query processors. Efforts have been made to design query languages with proper semantics to facilitate query optimization and(More)
Joint analysis of medical data collected from different imaging modalities has become a common clinical practice. Therefore, image fusion techniques, which provide an efficient way of combining and enhancing information, have drawn increasing attention from the medical community. In this paper, we propose a novel cross-scale fusion rule for(More)
Most image database prototypes and products focus mainly on similarity searches over syntactic features of images. DISIMA aims at providing querying on both syntactic and semantic features of images. The content of an image is viewed as a set of salient objects (regions of interest). Salient objects are organized into two levels: physical salient objects(More)
We develop an adaptive active contour tracing algorithm for extraction of spinal cord from MRI that is fully automatic, unlike existing approaches that need manually chosen seeds. We can accurately extract the target spinal cord and construct the volume of interest to provide visual guidance for strategic rehabilitation surgery planning.
This paper presents a novel two-phase stereo matching algorithm using the random walks framework. At first, a set of reliable matching pixels is extracted with prior matrices defined on the penalties of different disparity configurations and Laplacian matrices defined on the neighbourhood information of pixels. Following this, using the reliable set as(More)
Many state-of-the-art fusion methods, combining details in images taken under different exposures into one well-exposed image, can be found in the literature. However, insufficient study has been conducted to explore how perceptual factors can provide viewers better quality of experience on fused images. We propose two perceptual quality measures: perceived(More)