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This paper presents a computational performance analysis of an accelerated medical image registration using Graphics Processing Units (GPUs). In our previous work, a multi-resolution approach using normalized mutual information (NMI) has proven to be useful in medical image registration. In this paper, we propose an acceleration of the NMI procedure using GPU implementation because of the parallel...
Recently, keypoint descriptors such as Scale Invariant Feature Transform (SIFT) have been proved promising in similarity retrieval of images, which adopts matching score as similarity. However, the matching score is easy to be decreased once there are little variances between image details, and hence lead to low retrieval performance. In this paper, we propose a novel retrieval approach that improves...
In this paper, we consider the problem of classifying a real world image to the corresponding object class based on its visual content via sparse representation, which is originally used as a powerful tool for acquiring, representing and compressing high-dimensional signals. Assuming the intuitive hypothesis that an image could be represented by a linear combination of the training images from the...
Based on the ideas of feature fusion and Kernel Canonical Correlation Analysis (KCCA), a novel framework for fusing global and local features on Automatic Target Recognition (ATR) algorithm is proposed. Firstly, the feature fusion method based on KCCA is established, then pseudo Zernike moments and Scale Invariant Feature Transform (SIFT) are extracted as global features and local features. K-means...
In this paper, we propose a method for removing motion blur and deringing from images, which can be applied to handle both the camera motion blur and the object motion blur. Fully taking the advantage of abundant information of blurred/noisy image pair, we can extract the alpha mattes of same objects in both burred image and noisy image, and then estimate the blur kernel of blurred image using the...
Blind image deconvolution is required in many applications of microscopy imaging, remote sensing, and astronomical imaging. The primary difficulty with blind image restoration is insufficient information. We propose a novel algorithm in the estimation of blur based on convex optimization theory and image information. How to extract the information from image is discussed in this paper. Finally, the...
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