In this paper, we propose a new primal-dual fixed point algorithm with dynamic stepsize (PDFP2ODSn) for solving convex minimization problems involving the sum of a smooth function with Lipschitzian gradient and the co...
详细信息
In this paper, we propose a new primal-dual fixed point algorithm with dynamic stepsize (PDFP2ODSn) for solving convex minimization problems involving the sum of a smooth function with Lipschitzian gradient and the composition of a nonsmooth convex function with a continuous linear operator. Based on modified Mann iteration and the firmly nonexpansive properties of the proximity operator, we achieve the convergence of the proposed algorithm. Moreover, we give the connection of the proposed algorithm with other existing PDFP2O (Chen et al. in Inverse Probl 29:025011-025033, 2013). Finally, we illustrate the efficiency of PDFP2ODSn through some numerical examples on the CT image reconstruction problem. Numerical results show that our iterative algorithm (PDFP2ODS) performs better than the original one (PDFP2O).
Melanoma is a deadly form of skin cancer that is often undiagnosed or misdiagnosed as a benign skin lesion. Its early detection is extremely important, since the life of patients with melanoma depends on accurate and ...
详细信息
Depth image based rendering (DIBR) is the most widely used technology among synthesis algorithms. Hole filling is a challenge in producing desirable synthesized images. In this paper, we propose an enhanced non local ...
详细信息
ISBN:
(数字)9781510630765
ISBN:
(纸本)9781510630765
Depth image based rendering (DIBR) is the most widely used technology among synthesis algorithms. Hole filling is a challenge in producing desirable synthesized images. In this paper, we propose an enhanced non local mean based hole filling method. Color, gradient and depth information is combined to select the optimal candidate patches. The missing information from holes is then formed by aggregating multiple candidate patches. Furthermore, an efficient invalid pixel classification method based on their chararcteristics is proposed to divide invalid pixels into three types, and use different methods to fill them, and reduce the computational load of the hole filling unit. The results show that the proposed method has a better robustness and performance for hole filling in DIBR systems than other hole filling based on algorithms.
This paper combines supervised linear unmixing and deconvolution problems to increase the resolution of the abundance maps for industrial imaging systems. The joint unmixing-deconvolution (JUD) algorithm is introduced...
详细信息
ISBN:
(纸本)9789082797039
This paper combines supervised linear unmixing and deconvolution problems to increase the resolution of the abundance maps for industrial imaging systems. The joint unmixing-deconvolution (JUD) algorithm is introduced based on the Tikhonov regularization criterion for offline processing. In order to meet the needs of industrial applications, the proposed JUD algorithm is then extended for online processing by using a block Tikhonov criterion. The performance of JUD is increased by adding a non-negativity constraint which is implemented in a fast way using the quadratic penalty method and fast Fourier transform. The proposed algorithm is then assessed using both simulated and real hyperspectral images.
Cardiac diffusion tensor imaging (CDTI) provides unique information on the structure, organization, and integrity of the myocardium. However, the inherently low signal-to-noise ratio (SNR) limits the accuracy in param...
详细信息
ISBN:
(纸本)9781665423144;9781665446235
Cardiac diffusion tensor imaging (CDTI) provides unique information on the structure, organization, and integrity of the myocardium. However, the inherently low signal-to-noise ratio (SNR) limits the accuracy in parameter estimations. Recently, several post-processingalgorithms have been proposed to improve image quality in brain DTI, but their performance is unknown in CDTI. This paper evaluates three different denoising algorithms (ANLM, LPCA, and MPPCA) in CDTI regarding image quality and accuracy of parameters with simulation and ex-vivo experiments. We add white Gaussian noise to the simulated DWI images and average ex-vivo data with various repetitions to imitate CDTI images with different SNRs. Then, denoising methods are applied, and the performance is evaluated by SNR and RMSE. The results show that the SNR is improved by 72.38%, 127.01%, 0.6% in simulation, and 327.38%, 474.56%, 173.19% in ex-vivo experiments by the three methods, respectively. The uncertainty of parameters is reduced by all three algorithms in the ex-vivo experiment.
Conformal prediction uses the degree of strangeness (nonconformity) of new data instances to determine the confidence values of new predictions. We propose an inductive conformal predictor for sparse coding classifier...
详细信息
ISBN:
(纸本)9781479981311
Conformal prediction uses the degree of strangeness (nonconformity) of new data instances to determine the confidence values of new predictions. We propose an inductive conformal predictor for sparse coding classifiers, referred to as ICP-SCC. Our contribution is twofold: first, we present two nonconformity measures that produce reliable confidence values;second, we propose a batch mode active learning algorithm within the conformal prediction framework to improve classification performance by selecting training instances based on two criteria, informativeness and diversity. Experiments conducted on face and object recognition databases demonstrate that ICP-SCC improves the classification accuracy of state-of-the-art dictionary learning algorithms while producing reliable confidence values.
Hash algorithms have been widely used for cryptography. It has been impossible to decrypt the ciphertexts generated through hash algorithms, as an operation that damages the original text is performed. However, variou...
详细信息
ISBN:
(纸本)9783030190637;9783030190620
Hash algorithms have been widely used for cryptography. It has been impossible to decrypt the ciphertexts generated through hash algorithms, as an operation that damages the original text is performed. However, various methods of attack occurred over time after the algorithm was developed. The vulnerability of SHA1 (an old hash algorithm) has been revealed, and there has been a great deal of data available for dictionary attacks. Although the industry has been gradually refraining from using SHA1, it remains in use in some existing systems for various reasons. For example, when problems resulting from service interruption or mass update are critical, updating the encryption algorithm can be a burden. In this study, we aim to increase the complexity of ciphertexts by postprocessing hash ciphertext. For that, image salting techniques are used using two-dimensional array masking. This will allow the use of hash ciphertexts with increased complexity in some devices that are forced to use old hash algorithms for various reasons.
Blind image denoising is an important yet very challenging problem in computer vision due to the complicated acquisition process of real images. In this work we propose a new variational inference method, which integr...
详细信息
Blind image denoising is an important yet very challenging problem in computer vision due to the complicated acquisition process of real images. In this work we propose a new variational inference method, which integrates both noise estimation and image denoising into a unique Bayesian framework, for blind image denoising. Specifically, an approximate posterior, parameterized by deep neural networks, is presented by taking the intrinsic clean image and noise variances as latent variables conditioned on the input noisy image. This posterior provides explicit parametric forms for all its involved hyper-parameters, and thus can be easily implemented for blind image denoising with automatic noise estimation for the test noisy image. On one hand, as other data-driven deep learning methods, our method, namely variational denoising network (VDN), can perform denoising efficiently due to its explicit form of posterior expression. On the other hand, VDN inherits the advantages of traditional model-driven approaches, especially the good generalization capability of generative models. VDN has good interpretability and can be flexibly utilized to estimate and remove complicated non-i.i.d. noise collected in real scenarios. Comprehensive experiments are performed to substantiate the superiority of our method in blind image denoising.
The development of the modern world's information and communication technologies and their implementation in various industries are important, are essential to the creation of parallel algorithms for solving probl...
详细信息
Year after year drowning deaths are increasing tremendously, making it the 3rd leading cause of unintentional injury deaths worldwide. Drift prediction methodology is typically not used in river ecosystems and convent...
详细信息
ISBN:
(纸本)9781665439206
Year after year drowning deaths are increasing tremendously, making it the 3rd leading cause of unintentional injury deaths worldwide. Drift prediction methodology is typically not used in river ecosystems and conventional methods for human rescue do not account for feasible and faster human detection. Utilization of multiple sensor data in underwater human rescue applications can capacitate faster human detection. This paper discusses the design, implementation, and testing of such an underwater human detection system, which spots the victim drifting or drowning in freshwater ecosystems. The water flow sensor attached to this portable device can calculate drift distance to track down the victim. The ultrasonic sensor activates the underwater camera upon detecting an object, to facilitate real-time human localization. We performed real-time object detection on a custom dataset by applying DarkNet-53 pre-trained weights on YOLOv3 architecture and a mean Average Precision (mAP) of 98.0% was achieved. The system attained a detection depth of 5m. Combined action of drift distance calculator and YOLOv3 real-time detection model can speed up underwater human extrication.
暂无评论