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Compressive sensing (CS) has recently attracted much attention due to its unique feature of directly and simultaneously acquiring compressed and encrypted data based on their sparse or compressible properties. To securely transmit compressively sensed multimedia data over networks, it is required to support transcoder to securely convert compressed multimedia into several different types for diverse...
Face Hallucination is, one of a learning-based super-resolution technique that can reconstruct a high-resolution image using only one low-resolution image. However, there are often some detailed high-frequency components of the reconstructed image that cannot be recovered using this method. In this study, we proposed a high-frequency compensated face hallucination method for enhancing reconstruction...
Incremental principal component analysis (IPCA) has been of great interest in computer vision and machine learning. In this paper, we introduce a new incremental learning procedure for principal component analysis (PCA). The proposed method can keep an accurate track of the mean of the data, and can deal with a set of new observed data in batch each time in subspace updating. Furthermore, a weighting...
In this paper, we propose a penalized ℓ1 minimization algorithm for reconstructing a time-varying signal based on compressive sensing (CS) principles. The time-varying signal can be seen as a sequence of slow-changing frames. In the proposed algorithm, all frames of the sequence are sampled at an equal rate, which makes the encoder simpler than frame-categorized methods. We introduce a specialized...
In medical imaging, the data resolution is usually insufficient for accurate diagnosis in clinical medicine. Especially in most case, the resolution in the slice direction (Z direction) is much lower than that of the in-plane resolution (XY direction). Therefore it is difficult to construct isotropic voxels, which is very important in 3-D visualization systems, such as surgical system. In this paper,...
Assessment of image similarity is fundamentally important to numerous multimedia applications. The goal of similarity assessment is to automatically assess the similarities among images in a perceptually consistent manner. In this paper, we interpret the image similarity assessment problem as an information fidelity problem. More specifically, we propose a feature-based approach to quantify the information...
Theoretical analysis indicated FLOT resolution can be improved by angled incidence and detection. We developed an angled FLOT system and experimentally demonstrated its capability for depth-resolved fluorescence imaging in scattering medium.
Example-Based Super-Resolution is a learning-based technique that attempts to recover high-resolution (HR) image according to the corresponding relation in a set of training low-resolution (LR) and high-resolution image pairs prepared in advance. The conventional learning-based method for image super-resolution usually cannot achieve the high-frequency components accurately, which are lost in the...
We address an important issue of fully low-cost and low-complex video compression for use in resource-extremely limited sensors/devices. Conventional motion estimation-based video compression or distributed video coding (DVC) techniques all rely on the high-cost mechanism, namely, sensing/sampling and compression are disjointedly performed, resulting in unnecessary consumption of resources. That is,...
In direct volume rendering, specifying appropriate transfer functions to efficiently classify volumetric data is a challenging task. One of the main reasons is the lack of a feedback mechanism to indicate which parts of the specified transfer function actually contribute to the resulting image at the given viewpoint. In this paper we propose a novel image-driven mining approach that can compute the...
The task of visual tracking is to deal with dynamic image streams that change over time. For color object tracking, although a color object is a 3-order tensor in essence, little attention has been focused on this attribute. In this paper, we propose a novel Incremental Multiple Principal Component Analysis (IMPCA) method for online learning dynamic tensor streams. When newly added tensor set arrives,...
In this paper, a statistical texture modeling method is proposed for medical volumes. As the shapes of the human organ are very different from one case to another, 3D volume morphing is applied to normalize all the volume datasets to a same shape for removing shape variations. In order to deal with the problems of high-dimension and small number of medial samples, we propose an effective image compression...
In this paper, we formulate the problems of image copy detection and image recognition in terms of sparse representation. To achieve robustness, security, and efficient storage of image features, we propose to extract compact local feature descriptors via constructing the basis of the SIFT-based feature vectors extracted from the secure SIFT domain of an image. Image copy detection can be efficiently...
In medical imaging research fields, three-dimensional (3D) shape modeling and analysis of anatomic structures with fewer parameters is one of important issues, which can be used for computer assisted diagnosis, surgery simulation, visualization and many medical applications. The 3-D object shape or surface can be expressed by spherical harmonics. In this paper, we present a spherical harmonics based...
In this paper, we report our current progress results on computer assisted diagnostic (CAD) system, which consists of three units: database unit (statistical atlas of human anatomy), image processing unit (image enhancement, image segmentation, image registration), and visualization unit (volume rendering). In the database unit, we proposed a new method called generalized N-dimensional principal component...
In this paper, we apply iterative transform algorithms, namely the error reduction algorithm and the hybrid input-output algorithm, to retrieve missing data in 3D reconstruction from 2D crystal images. 3D protein structures are determined using cryo-electron microscopy (cryo-EM). Extremely strong noise in cryo-EM brings in unreliable artifacts and a limited number of projections leave missing components...
Super-resolution (SR) enhancement from multi-frame low-resolution (LR) images (multi-frame super-resolution) has been a well-studied topic in the literature. Image registration is the most important part for multi-frame super-resolution, and accurate alignment of LR images would contribute a critical role for the final success of SR image reconstruction. In this paper, we propose to combine the Principle...
Cone-beam CT (CBCT) scanners are based on volumetric tomography, using a 2D extended digital array providing an area detector. Compared to traditional CT, CBCT has many advantages, such as less X-ray beam limitation, high image accuracy, rapid scan time, etc. However, In CBCT images there are always some ring artifacts that appear as rings centered on the rotation axis. Due to the data of the constructed...
A new method about reconstructing the finite element model of artificial knee joint is presented in this article after the research on reverse engineering (RE for short). Firstly, on the basis of the prosthesis prototype, IMAGEWARE and PRO/E are used to deal with point cloud of prototype and then prosthesis model is reconstructed; secondly, based on CT of human knee joint, distal femur (DF for short)...
Effective background reconstruction is the key for real time traffic flow monitoring. High traffic density and complexity of background scene make reconstruction more difficult. Background estimation based on the median method is imprecise under a complex traffic flow condition. In this paper, a new background estimation method based on the similarity of background using parameters of gray mean and...
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