Super-resolution reconstruction for image sequences is a promising imageprocessing technology that using complementary information among a set of images to reconstruct a high-resolution *** super-resolution reconstru...
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ISBN:
(纸本)9781509009107
Super-resolution reconstruction for image sequences is a promising imageprocessing technology that using complementary information among a set of images to reconstruct a high-resolution *** super-resolution reconstruction algorithms have been studied in the literature to reconstruct a high-resolution *** this paper,first,after presenting a condensed introduction of image registration algorithms including Lucchese algorithm,Vandewalle algorithm and Keren algorithm,we experimentally compare the relative merits of these registration algorithms in terms of registration accuracy and noise ***,we experimentally compare four image reconstruction methods:projection onto convex sets method(POCS),iterative back-projection method(IBP),robust super resolution(Robust SR) and structure-adaptive normalized convolution(Structure-Adaptive NC),mainly in terms of Peak Signal to Noise Ratio(PSNR),in which salt and pepper noise is added in the low resolution *** is clearly demonstrated that the combination of Keren algorithm and Structure-Adaptive NC can achieve the best performance regarding the Lena image.
In this paper, an image segmentation method is presented to analyze the clusters of Computed Tomography (CT) image. Target image is divided to small parts called as observation screens. Principal Component Analysis (P...
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ISBN:
(纸本)9781509013531
In this paper, an image segmentation method is presented to analyze the clusters of Computed Tomography (CT) image. Target image is divided to small parts called as observation screens. Principal Component Analysis (PCA) is used for better representation of features about observation screens. The optimal number of component related with observation screen is determined by Horn's Parallel Analysis (PA). Besides, Local Standard Deviation (LSD) which is a method for extracting meaningful sub-features is applied to whole image for successful segmentation. The effect of segmentation success rate is analyzed by selected features. Consequently, a novel algorithm is proposed for minimizing total computation time and error of dimension reduction significantly. It is seen that the results of the algorithm are approximately same as conventional segmentation algorithms.
In this paper, we describe a modification of the previously developed on-board imageprocessing method applied to hyperspectral images. algorithms on which the method is based were finalized and parametrically adjuste...
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In this paper, we describe a modification of the previously developed on-board imageprocessing method applied to hyperspectral images. algorithms on which the method is based were finalized and parametrically adjusted. Computational experiments consider formation and storage specifics for hyperspectral images. It has been shown that the proposed method based on HGI-compression can be recommended for implementation in on-board processingsystems and transmission over communication channels.
Artificial motion and warping of images taken at long range is one of the most significant and troublesome effects of atmospheric turbulence. It is important to understand and model this effect correctly in order to: ...
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ISBN:
(数字)9781510604094
ISBN:
(纸本)9781510604087;9781510604094
Artificial motion and warping of images taken at long range is one of the most significant and troublesome effects of atmospheric turbulence. It is important to understand and model this effect correctly in order to: 1) fully characterize turbulence between the target and the observer, 2) devise efficient post-processing strategies for artificial motion correction, and 3) exploit information about statistics of this atmospheric motion to distinguish between real and fake movement in a scene. This paper discusses two types of motion: G-tilt and Z-tilt, highlighting the differences between them. Optimal image block size for de-warping algorithms and bandwidth considerations are given special attention. Finally, strategies for turbulence characterization based on differential image motion are discussed.
In this study, we have designed a GPGPU (General-Purpose Graphics processing Unit)-based algorithm for determining the minimum distance from the tip of a CUSA (Cavitron Ultrasonic Surgical Aspirator) scalpel to the cl...
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The aim of this article is to present a method to detect visual objects from color digital images by volumetric segmentation. We will discuss algorithms for visual and multimedia computing. The problem of partitioning...
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imageprocessingalgorithms applied on programmable embedded systems very often do not meet the given constraints in terms of real time capability. Mapping these algorithms to reconfigurable hardware solves this issue...
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image segmentation is a key component in many computer vision systems, and it is recovering a prominent spot in the literature as methods improve and overcome their limitations. The outputs of most recent algorithms a...
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ISBN:
(纸本)9781467388511
image segmentation is a key component in many computer vision systems, and it is recovering a prominent spot in the literature as methods improve and overcome their limitations. The outputs of most recent algorithms are in the form of a hierarchical segmentation, which provides segmentation at different scales in a single tree-like structure. Commonly, these hierarchical methods start from some low-level features, and are not aware of the scale information of the different regions in them. As such, one might need to work on many different levels of the hierarchy to find the objects in the scene. This work tries to modify the existing hierarchical algorithm by improving their alignment, that is, by trying to modify the depth of the regions in the tree to better couple depth and scale. To do so, we first train a regressor to predict the scale of regions using mid-level features. We then define the anchor slice as the set of regions that better balance between over-segmentation and under-segmentation. The output of our method is an improved hierarchy, re-aligned by the anchor slice. To demonstrate the power of our method, we perform comprehensive experiments, which show that our method, as a post-processing step, can significantly improve the quality of the hierarchical segmentation representations, and ease the usage of hierarchical image segmentation to high-level vision tasks such as object segmentation. We also prove that the improvement generalizes well across different algorithms and datasets, with a low computational cost.
The static image and video information compression algorithms development over the last 15-20 years, as well as standardized and non-standardized formats for data storage and transmission have been analyzed;the main f...
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ISBN:
(数字)9783319393452
ISBN:
(纸本)9783319393452;9783319393445
The static image and video information compression algorithms development over the last 15-20 years, as well as standardized and non-standardized formats for data storage and transmission have been analyzed;the main factors affecting the further development of approaches that eliminate the redundancy of transmitted and stored visual information have been studied. The conclusion on the current prospects for the development of image compression technologies has been made. New approaches that use new low-level quasi-orthogonal matrices as transform operators have been defined. The advantages of such approaches opening new fundamentally different opportunities in the field of applied processing of digital visual information have been identified and presented.
As massive open online courses (MOOCs) and online intelligent tutoring systems(ITS) have become increasingly widespread, the number of learners enrolled in online courses has shown explosive growth. However, these lea...
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