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Conventional unsupervised image segmentation methods use color and geometric information and apply clustering algorithms over pixels. They preserve object boundaries well but often suffer from over-segmentation due to noise and artifacts in the images. In this paper, we contribute on a preprocessing step for image smoothing, which alleviates the burden of conventional unsupervised image segmentation...
The traditional CRT based algorithms have been proposed to solve the problem of range estimation with multi-frequency phase unwrapping, where the wavelengths of the multi-frequency signals should to be pair-wisely co-prime after they are divided by their greatest common divisor (GCD). To get a robust reconstruction result, the upper bound of the remainder errors should be smaller than a quarter of...
Due to the explosive growth of visual data and the raised urgent needs for more efficient nearest neighbor search methods, hashing methods have been widely studied in recent years. However, parameter optimization of the hash function in most available approaches is tightly coupled with the form of the function itself, which makes the optimization difficult and consequently affects the similarity preserving...
In the field of oncology, simultaneous Positron-Emission-Tomography/Magnetic Resonance (PET/MR) scanners offer a great potential for improving diagnostic accuracy. However, to achieve a high Signal-to-Noise Ratio (SNR) for an accurate lesion detection and quantification in the PET/MR images, one has to overcome the induced respiratory motion artifacts. The simultaneous acquisition allows performing...
Compression of encrypted data has attracted considerable research interests nowadays due to distributed processing and cloud computing. In this work, we propose a novel lossy compression scheme for encrypted gray-scale images. The original image is first divided into non-overlapping blocks. Then, it is encrypted by a modulo-256 addition and block permutation. In compression phase, the spatial correlation...
In this paper, we present a novel pixel-level color-image fusion method with extension of the joint sparsity model which exploits the inter-correlations among the R, G and B planes. The objective is to achieve the colors more natural for the fused images, compared to individually reconstructing the R, G, B images. This paper also demonstrates an extension of the fusion algorithm to the proper handling...
In this paper, we present an effective algorithm for image interpolation. Our algorithm first calculates basis function of multivariate spline, on this basis, builds an operator applied to image interpolation. Finally, by experiment our algorithm reconstructs different interval sampled images, and compares with bilinear interpolation and double cubic convolution interpolation methods respectively...
To obtain an image with every object in focus, we always need to fuse images taken from the same view point with different focal settings. Multiresolution transforms, such as pyramid decomposition and wavelet, are usually used to solve this problem. In this paper, a sparse representation-based multifocus image fusion method is proposed. In the method, first, the source image is represented with sparse...
The 3-d motion information is significant in the study of aeolian sand transport. This paper describes the way to obtain the 3-d velocity field of moving sand by means of Stereo PIV. Double CCD-cameras are used to capture the sand particle images with the Scheimpflug configuration. The mapping function of each image plane to object plane resulted from the 3-d calibration method. Especially the evaluation...
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