Ordinary Lucy-Richardson (LR) restoration algorithms are used to restore high SNR degraded images including astronomical images and achieve good results. The algorithms are very sensitive to noises and use the assumpt...
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Deep learning based object detection algorithms have been applied in various fields of life. As a representative of one-stage detection algorithms, YOLO series algorithms are highly favored for their fast *** resolve ...
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In this paper, we present two novel medical image enhancement algorithms. The first, a global image enhancement algorithm, utilizes an alpha-trimmed mean filter as its backbone to sharpen images. The second algorithm ...
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ISBN:
(纸本)9780819479259
In this paper, we present two novel medical image enhancement algorithms. The first, a global image enhancement algorithm, utilizes an alpha-trimmed mean filter as its backbone to sharpen images. The second algorithm uses a cascaded unsharp masking technique to separate the high frequency components of an image in order for them to be enhanced using a modified adaptive contrast enhancement algorithm. Experimental results from enhancing electron microscopy, radiological, CT scan and MRI scan images, using the MATLAB environment, are then compared to the original images as well as other enhancement methods, such as histogram equalization and two forms of adaptive contrast enhancement. An imageprocessing scheme for electron microscopy images of Purkinje cells will also be implemented and utilized as a comparison tool to evaluate the performance of our algorithm.
We consider the problem of improving contour detection by filling gaps between collinear contour pieces. A fast algorithm is proposed which takes into account local edge orientation and local curvature. Each edge poin...
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ISBN:
(纸本)9780819469847
We consider the problem of improving contour detection by filling gaps between collinear contour pieces. A fast algorithm is proposed which takes into account local edge orientation and local curvature. Each edge point is replaced by a curved elongated patch, whose orientation and curvature match the local edge orientation and edge. The proposed contour completion algorithm is integrated in a multiresolution framework for contour detection. Experimental results show the superiority of the proposed method to other well-established approaches.
Phase diversity algorithms allow wavefront and an estimate of the scene to be reconstructed from multiple images with a known phase change between measurements. These algorithms rely on sampling requirements that are ...
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ISBN:
(纸本)9780819492166
Phase diversity algorithms allow wavefront and an estimate of the scene to be reconstructed from multiple images with a known phase change between measurements. These algorithms rely on sampling requirements that are frequently not met in remote sensing imaging systems. It is demonstrated that super-resolution pre-processing of imagery from undersampled systems can effectively increase the sampling, thereby allowing application of traditional phase diversity algorithms. Experimental results are presented for both a point object and an extended scene.
This article presents and compares optimized implementations of two optical flow algorithms on several target boards comprising multi-core SIMD processors and GPUs. The two algorithms are Horn-Schunck (HS) and TV-L1, ...
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ISBN:
(纸本)9781538682371
This article presents and compares optimized implementations of two optical flow algorithms on several target boards comprising multi-core SIMD processors and GPUs. The two algorithms are Horn-Schunck (HS) and TV-L1, and have been chosen because they are both well-known, and because of their different computational complexity and accuracy. For both algorithms, we have made parallel optimized SIMD implementations, while HS has also been implemented on GPUs. For each algorithm, the comparison between the different versions and target boards is carried out in a two-dimensional fashion: in terms of computing speed-in order to achieve real-time computation-and in terms of energy consumption since we target embedded systems. The results show that for HS, the GPUs are the most efficient in both dimensions, able to process in realtime performances (25 frames per second) up to 8Mpix images for 0.35J per image, against 1.8Mpix images for 0.24J per image on CPU. The results also highlight the impact of optimizations on TV-L1: far slower than HS without optimization, it can almost match its performance after optimization on CPU, and can achieve real-time performances with 0.25J for 1.4Mpix images. We hope these results will help developers design optical flow embedded systems.
The research on image presentation and imageprocessingalgorithms in Contourlet domain has been increasingly wide and deep. Combined frequency band property of different direction and the perfect coefficient features...
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ISBN:
(纸本)9781424447541
The research on image presentation and imageprocessingalgorithms in Contourlet domain has been increasingly wide and deep. Combined frequency band property of different direction and the perfect coefficient features of Contourlet transform, a new method of image quality. assessment based on Structural Similarity (SSIM) and human vision system (HVS)-CT-SSIM is proposed in this paper. Theory analysis and experimental results show that the proposed CT-SSIM is more accurate and has better correlation with the subjective assessment of human beings. Also it can easily be embedded in imageprocessingalgorithms in Contourlet domain, to guide and optimize the processingalgorithms.
In the new wave of artificial intelligence, deep learning is impacting various industries. As a closely related area, optimization algorithms greatly contribute to the development of deep learning. But the reverse app...
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In the new wave of artificial intelligence, deep learning is impacting various industries. As a closely related area, optimization algorithms greatly contribute to the development of deep learning. But the reverse applications are still insufficient. Is there any efficient way to solve certain optimization problem through deep learning? The key is to convert the optimization to a representation suitable for deep learning. In this article, a traveling salesman problem (TSP) is studied. Considering that deep learning is good at imageprocessing, an image representation method is proposed to transfer a TSP to an image. Based on samples of a ten city TSP, a fully convolutional network (FCN) is used to learn the mapping from a feasible region to an optimal solution. The training process is analyzed and interpreted through stages. A visualization method is presented to show how an FCN can understand the training task of a TSP. Once the training is completed, no significant effort is required to solve a new TSP and the prediction is obtained on the scale of milliseconds. The results show good performance in finding the global optimal solution. Moreover, the developed FCN model has been demonstrated on TSP's with different city numbers, proving excellent generalization performance.
GPGPU (General Purpose computing on Graphic processing Unit) systems attract a great deal of attention, which are used for general-purpose computations like numerical calculations as well as graphic processing, but th...
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ISBN:
(纸本)9781467307499
GPGPU (General Purpose computing on Graphic processing Unit) systems attract a great deal of attention, which are used for general-purpose computations like numerical calculations as well as graphic processing, but the peak power consumption of the GPU is relatively high. On the other hand, fractal image coding is one of the most prominent compression technologies. It can be also used for industrial applications like image indexing methods and image retrieval methods. In this paper, we implement parallel programs for the fractal image coding algorithms on GPGPU systems by using CUDA (Compute Unified Device Architecture) and discuss the power-aware evaluation of the application. We also consider the availability of the GPU from the point of view of the green computing.
We present a platform that will aid researchers in developing algorithms for specific (primarily imageprocessing) tasks by providing training data sets with ground truth and with providing evaluation of the outputs o...
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ISBN:
(纸本)9781479972807
We present a platform that will aid researchers in developing algorithms for specific (primarily imageprocessing) tasks by providing training data sets with ground truth and with providing evaluation of the outputs of the algorithms in an objective manner under identical conditions using standardized measures.
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