A review of modern optimal and quasi-optimal algorithms for radiometric signal processing, which provide images with a high spatial resolution is given. It is shown that the high resolution is achieved with ultra-wide...
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ISBN:
(纸本)9781479985579
A review of modern optimal and quasi-optimal algorithms for radiometric signal processing, which provide images with a high spatial resolution is given. It is shown that the high resolution is achieved with ultra-wideband or multi-band time or space-time signal processing. Analytical expressions for the limiting error of image estimation, ambiguity functions and potential fluctuation sensitivity of systems designed according to the algorithms are derived.
Medical images communicate imperative information to the doctors about a patient's health situation. Internet broadcasts these medical images to inaccessible sites of the globe which are inspected by specialist do...
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ISBN:
(纸本)9781479961085
Medical images communicate imperative information to the doctors about a patient's health situation. Internet broadcasts these medical images to inaccessible sites of the globe which are inspected by specialist doctors. But data transmissions through unsecured web invoke validation problems for any image data. Medical images that are transmitted through the internet must be watermarked with patient pictures for substantiation by the doctors to ascertain the medical image. Watermarking medical images necessitate attentive adjustments to protect the information in the medical images with patient image watermarks. The medical images are used as an envelope image in the watermarking process which is visible on the network. These envelope medical images are watermarked with patient images in wavelet domain there by using the BAT algorithm form optimizing the embedding process for peak signal to noise ratio (psnr) and normalized cross correlation coefficient (ncc) values. The medical image envelope and letter inside envelope i.e. watermark image are transformed into wavelet domain and are mixed using scaling factor alpha which is termed as embedding strength. BAT algorithm is an optimization algorithm specialized in optimizing the values of peak-signal-to-noise ratio for a particular value of alpha, the embedding watermark strength. Finally these watermarked medical images are put on the network along with the secret key that will be used for extraction. At the receiving the embedded watermark is extracted using 2DWT using the embedding strength value using BAT algorithm. The robustness of the proposed watermarking techniques is tested with various attacks on the watermarked medical images. Peak-Signal-to-Noise ratios and Normalized cross correlation coefficients are computed to accesses the quality of the watermarked medical images and extracted patient images. The results are produced for three types of medical images with one patient image watermarks using single key b
Recently various algorithms for building of three-dimensional maps of indoor environments have been proposed. In this work we use a Kinect camera that captures RGB images along with depth information for building thre...
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ISBN:
(纸本)9781628417654
Recently various algorithms for building of three-dimensional maps of indoor environments have been proposed. In this work we use a Kinect camera that captures RGB images along with depth information for building three-dimensional dense maps of indoor environments. Commonly mapping systems consist of three components;that is, first, spatial alignment of consecutive data frames;second, detection of loop-closures, and finally, globally consistent alignment of the data sequence. It is known that three-dimensional point clouds are well suited for frame-to-frame alignment and for three-dimensional dense reconstruction without the use of valuable visual RGB information. A new fusion algorithm combining visual features and depth information for loop-closure detection followed by pose optimization to build global consistent maps is proposed. The performance of the proposed system in real indoor environments is presented and discussed.
Big data is emerging in all the fields of science. Scope of data analysis is not limited to the analysis of archival data, rather is it more concerned towards giving better decisions on the bases of visualization of a...
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ISBN:
(纸本)9781509001484
Big data is emerging in all the fields of science. Scope of data analysis is not limited to the analysis of archival data, rather is it more concerned towards giving better decisions on the bases of visualization of analytic reports. Traditional systems are only dealing with 2 v's of big data, i.e. volume and variety. In order to make decisions more fast 3(rd) v i.e. velocity of data is more effective and convenient characteristic for analysis. Big data analytics is helping businesses with millions of customers to identify customer needs by bringing unstructured data into the arena. Data Analytics techniques can help organizations make sense of the data gain competitive advantage. This paper gives a method of improving speed of decision making by analyzing real time streams for effective Business Intelligence with traditional system and to give fast results for improvised decision making.
Key point correspondence plays an important role in lunar surface imageprocessing. Since lunar surface images often contain obvious illumination changes, noisy points and repetitive patterns, traditional appearance b...
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ISBN:
(纸本)9781467384155
Key point correspondence plays an important role in lunar surface imageprocessing. Since lunar surface images often contain obvious illumination changes, noisy points and repetitive patterns, traditional appearance based algorithms may fail when local appearance descriptors become less distinctive. In this paper, we introduce a graph matching based algorithm to tackle this problem. First, by incorporating structural information, key point sets in lunar surface images are represented by graphs. Then key point correspondence is formulated as a specific graph matching problem which aims to find a specified number of best assignments, and effectively approximately solved. Finally, an outlier assignment elimination method is proposed based on the affine invariance assumption. Simulations on both benchmark datasets and lunar surface images witness the effectiveness of the proposed method.
Automatic image annotation is the computer vision task of assigning a set of appropriate textual tags to a novel image. The aim is to eventually bridge the semantic gap of visual and textual representations with the h...
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ISBN:
(纸本)9781467385640
Automatic image annotation is the computer vision task of assigning a set of appropriate textual tags to a novel image. The aim is to eventually bridge the semantic gap of visual and textual representations with the help of these tags. This also has applications in designing scalable image retrieval systems and providing multilingual interfaces. Though a wide varieties of powerful machine learning algorithms have been explored for the image annotation problem in the recent past, nearest neighbor techniques still yield superior results to them. A challenge ahead of the present day annotation schemes is the lack of sufficient training data. In this paper, an active Learning based image annotation model is proposed. We leverage the image-toimage and image-to-tag similarities to decide the best set of tags describing the semantics of an image. The advantages of the proposed model includes: (a). It is able to output the variable number of tags for images which improves the accuracy. (b). It is effectively able to choose the difficult samples that needs to be manually annotated and thereby reducing the human annotation efforts. Studies on Corel and IAPR TC-12 datasets validate the effectiveness of this model.
Measuring the distances is a key problem in many imageanalysis algorithms. This is especially true for image segmentation. It provides a basis for the decision whether two image points belong to a single or to two dif...
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Biometric systems have great importance in modern society. Today, we can find biometric systems using hardware technologies to provide an increasingly fast response. Partly this is possible due to the use of algorithm...
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Solving real world problems with embedded neural networks requires both training algorithms that achieve high performance and compatible hardware that runs in real time while remaining energy efficient. For the former...
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Solving real world problems with embedded neural networks requires both training algorithms that achieve high performance and compatible hardware that runs in real time while remaining energy efficient. For the former, deep learning using backpropagation has recently achieved a string of successes across many domains and datasets. For the latter, neuromorphic chips that run spiking neural networks have recently achieved unprecedented energy efficiency. To bring these two advances together, we must first resolve the incompatibility between backpropagation, which uses continuous-output neurons and synaptic weights, and neuromorphic designs, which employ spiking neurons and discrete synapses. Our approach is to treat spikes and discrete synapses as continuous probabilities, which allows training the network using standard backpropagation. The trained network naturally maps to neuromorphic hardware by sampling the probabilities to create one or more networks, which are merged using ensemble averaging. To demonstrate, we trained a sparsely connected network that runs on the TrueNorth chip using the MNIST dataset. With a high performance network (ensemble of 64), we achieve 99.42% accuracy at 108 mu J per image, and with a high efficiency network (ensemble of 1) we achieve 92.7% accuracy at 0.268 mu J per image.
In this paper a method for estimating the motion camcorder or platform used in imageprocessing tasks to determine the motion parameters is proposed. A method for determining and shaping optical flow weighted measurem...
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ISBN:
(纸本)9785919950233
In this paper a method for estimating the motion camcorder or platform used in imageprocessing tasks to determine the motion parameters is proposed. A method for determining and shaping optical flow weighted measurements for image blocks is proposed. The effectiveness of the proposed method is shown on the basis of numerical simulation data for test images. The methods and algorithms described in this paper are versatile enough and are implemented in various fields.
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