Current Issue : July - September Volume : 2018 Issue Number : 3 Articles : 6 Articles
This paper proposes an object-tracking algorithm with multiple randomlygenerated\nfeatures. We mainly improve the tracking performance which is\nsometimes good and sometimes bad in compressive tracking. In compressive\ntracking, the image features are generated by random projection. The resulting\nimage features are affected by the random numbers so that the results of\neach execution are different. If the obvious features of the target are not captured,\nthe tracker is likely to fail. Therefore the tracking results are inconsistent\nfor each execution. The proposed algorithm uses a number of different\nimage features to track, and chooses the best tracking result by measuring the\nsimilarity with the target model. It reduces the chances to determine the target\nlocation by the poor image features. In this paper, we use the Bhattacharyya\ncoefficient to choose the best tracking result. The experimental results show\nthat the proposed tracking algorithm can greatly reduce the tracking errors.\nThe best performance improvements in terms of center location error,\nbounding box overlap ratio and success rate are from 63.62 pixels to 15.45\npixels, from 31.75% to 64.48% and from 38.51% to 82.58%, respectively....
Objective. Kinetic modeling of dynamic 11C-acetate PET imaging provides quantitative information for myocardium assessment.\nThe quality and quantitation of PET images are known to be dependent on PET reconstruction methods. This study aims to\ninvestigate the impacts of reconstruction algorithms on the quantitative analysis of dynamic 11C-acetate cardiac PET imaging.\nMethods. Suspected alcoholic cardiomyopathy patients (...
Air pollution presents unprecedentedly severe challenges to humans today. Various measures have been taken to monitor pollution\nfrom gas emissions and the changing atmosphere, of which imaging is of crucial importance. By images of target scenes, intuitional\njudgments and in-depth data are achievable. However, due to the limitations of imaging devices, effective and efficient monitoring\nwork is often hindered by low-resolution target images. To deal with this problem, a superresolution reconstruction method was\nproposed in this study for high-resolution monitoring images. It was based on the idea of sparse representation. Particularly,\nmultiple dictionary pairs were trained according to the gradient features of samples, and one optimal pair of dictionaries was\nchosen to reconstruct by judging the weighting of the information in different directions. Furthermore, the K-means singular\nvalue decomposition algorithm was used to train the dictionaries and the orthogonal matching pursuit algorithm was employed\nto calculate the sparse coding coefficients. Finally, the experiment�s results demonstrated its advantages in both visual fidelity\nand numerical measures....
Image super-resolution (SR) reconstruction is to reconstruct a high-resolution\n(HR) image from one or a series of low-resolution (LR) images in the same\nscene with a certain amount of prior knowledge. Learning based algorithm is\nan effective one in image super-resolution reconstruction algorithm. The core\nidea of the algorithm is to use the training examples of image to increase the\nhigh frequency information of the test image to achieve the purpose of image\nsuper-resolution reconstruction. This paper presents a novel algorithm for\nimage super resolution based on morphological component analysis (MCA)\nand dictionary learning. The MCA decomposition based SR algorithm utilizes\nMCA to decompose an image into the texture part and the structure part and\nonly takes the texture part to train the dictionary. The reconstruction of the\ntexture part is based on sparse representation, while that of the structure part\nis based on more faster method, the bicubic interpolation. The proposed method\nimproves the robustness of the image, while for different characteristics\nof textures and structure parts, using a different reconstruction algorithm,\nbetter preserves image details, improve the quality of the reconstructed image....
TOFD (time of flight diffraction) is a kind of weld defect detection technology by using ultrasonic diffraction wave signal. Because\nthe diffraction intensity is far less than ultrasonic echo wave intensity, thus, the noise contained in TOFD signal is fairly large, and\nthe formed image is not clear enough. Therefore, it is difficult to determine the size of defects accurately. In this paper, a method of\nnoise reduction of TOFD signal and improving the resolution of the image are discussed based on the combination of wavelet\nthresholding and image registration. Wavelet multiresolution analysis method is adopted and the A-scan signal is decomposed\ninto different frequency components. We propose a new threshold function to process the wavelet coefficients, which guarantees\nto denoise while preserving the useful information as much as possible. Setting up the ultrasonic TOFD inspection system and\nthe image data with randomly distributed noise can be obtained via fine shake of the probes during testing. Then, image\nregistration based on maximum correlation and blending is adopted to eliminate the noise in further step. The result shows that\nthe proposed method can achieve denoising, together with resolution enhancement....
We propose a two-step integral imaging coding based three-dimensional (3D) information encryption approach in this paper. In\nthis approach, a synthetic aperture integral imaging system is applied to acquire a set of parallax images including spatial and\nangular information of 3D scene. In the encryption process, two-step coding is performed. In the first step, the acquired parallax\nimages are encrypted firstly by double random-phase coding in the Fresnel domain. In the second step, these encrypted parallax\nimages are encoded into a cipher image bymapping algorithmwhich is used to generate elemental image array of integral imaging.\nIn the decryption process, an inverse operation is performed. The experimental results demonstrate the feasibility, security, and\nrobustness of the proposed approach....
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