In this paper, the method of two TDI (Time Delay Integration) CCD intersection is proposed to achieve the location of light target in a large field. Frame difference method combined with OTSU threshold segmentation al...
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In this paper, the method of two TDI (Time Delay Integration) CCD intersection is proposed to achieve the location of light target in a large field. Frame difference method combined with OTSU threshold segmentation algorithm is proposed to identify the image with light target. Besides, in order to reduce the storage capacity, we carry out binarization processing on target image. For getting the position of the light target in target image, the grayscale centroid algorithm is presented. In this paper, TDI CCD with high-speed and high-sensitivity is utilized as image sensor, and MATLAB is selected as image processing software. In our test, we carry on image processing by using the above algorithm with the images of 8192*32 pixels acquired from the 320m*240m field by two TDI CCD cameras in MATLAB. With the method of intersection of two TDI CCD, the location error is within 5% compared with the result achieved by total station instrument.
In this paper, an effort is made to enlarge a low resolution image. This paper presents an effective novel single image super resolution approach to recover a high resolution image from a single low resolution input i...
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In this paper, an effort is made to enlarge a low resolution image. This paper presents an effective novel single image super resolution approach to recover a high resolution image from a single low resolution input image. The approach is based on an Iterative back projection (IBP) method combined with the Canny Edge Detection and error difference image to recover high frequency information. This method is applied on different natural gray images and compared with different existing image super resolution approaches. Simulation results show that the proposed algorithm can more accurately enlarge the low resolution image than previous approaches. Proposed algorithm increases the PSNR and decreases MSE and MAE compared to other existing algorithms and also improves visual quality of an image considerably.
We analyze some key technologies in this paper, including technological convergence of CDN-P2P, Operation and release platform technology, online video database, the realization of three-screen interaction, and RIA pl...
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We analyze some key technologies in this paper, including technological convergence of CDN-P2P, Operation and release platform technology, online video database, the realization of three-screen interaction, and RIA platform, etc. We also build a uniform data access layer for three-screen interaction. An architecture of Omnimedia Release Operation Platform based on LAMP architecture is proposed and the functional analysis and system design of online video database system, Content Management System, User Management System, Ad Management System, and Operations support management systems are completed in this paper. An Omnimedia Release Operation Platform that can meet all audio and video needs is constructed at the same time.
Field-programmable gate arrays (FPGAs) are widely used in telecommunication due their substantial computational power and flexibly designed architecture. These features become especially important for applications of ...
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Field-programmable gate arrays (FPGAs) are widely used in telecommunication due their substantial computational power and flexibly designed architecture. These features become especially important for applications of low transmission latency such as those supported by Distributed Multimedia Plays (DMP) architecture. Thus FPGAs are chosen in this work as the core building block of the system. Complex multi-node telecommunication systems require special design methodology contrary to small ICT applications usually implemented in HDL. The methodology should be based on the appropriate tools from FPGA vendors for support and maintenance. This paper presents an architecture of a module to be embedded in all the FPGA-based nodes constituting a platform for the Real Time internetbased on DMP. It is designed using an embedded development kit natively supported by Xilinx and flexible in available cores. We present the implementation results of the network-node module and the description of PCIe-based protocol for inter-FPGA communication.
This paper proposes a novel content-basedimage retrieval technique, which facilitates short-term (intra-query) and long-term (inter-query) learning processes by integrating accumulated users' historical relevance...
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This paper proposes a novel content-basedimage retrieval technique, which facilitates short-term (intra-query) and long-term (inter-query) learning processes by integrating accumulated users' historical relevance feedback-based semantic knowledge. The history is efficiently represented as a dynamic semantic feature of the images. As such, the high-level semantic similarity measure can be dynamically adapted based on the semantic relevance derived from the dynamic semantic features. The short-term relevance feedback technique can benefit from long-term learning. Our extensive experiments show that the proposed system outperforms three peer systems in the context of both correct and erroneous relevance feedback.
A novel image inpainting algorithm based on edge reconstruction using combined approach capable to restore both image texture and structure is proposed in this paper. For edge and boundary detection and recovery a mul...
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A novel image inpainting algorithm based on edge reconstruction using combined approach capable to restore both image texture and structure is proposed in this paper. For edge and boundary detection and recovery a multi-stage edge detection procedure based on cubic splines is used. The choice of the current pixel to be recovered is decided using the fast marching approach. The Telea method or the exemplar based method are used after this depending on the classification of the regions where to-be-restored pixel is located. The performance of the proposed approach is demonstrated via several examples, showing the effectiveness of the proposed algorithm in removal of small and large objects from the test images.
Recently, content basedimage retrieval (CBIR) has gained active research focus due to wide applications such as crime prevention, medicine, historical research and digital libraries. With digital explosion, image col...
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Recently, content basedimage retrieval (CBIR) has gained active research focus due to wide applications such as crime prevention, medicine, historical research and digital libraries. With digital explosion, image collections in databases in distributed locations over the internet pose a challenge to retrieve images that are relevant to user queries efficiently and accurately. It becomes increasingly important to develop new CBIR techniques that are effective and scalable for real-time processing of very large image collections. To address this, the paper proposes a novel MapReduce neural network framework for CBIR from large data collection in a cloud environment. We adopt natural language queries that use a fuzzy approach to classify the colour images based on their content and apply Map and Reduce functions that can operate in cloud clusters for arriving at accurate results in real-time. Preliminary experimental results for classifying and retrieving images from large data sets were quite convincing to carry out further experimental evaluations.
A robust color image watermarking scheme is proposed, in which a color watermark is embedded into a color image. Principle component analysis is used to uncorrelate the R, G and B channels of both the images. Each cha...
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ISBN:
(纸本)9781467317139
A robust color image watermarking scheme is proposed, in which a color watermark is embedded into a color image. Principle component analysis is used to uncorrelate the R, G and B channels of both the images. Each channel of color watermark is embedded into singular values of corresponding channel of cover image after discrete wavelet decomposition. As original image is required at the time of extraction of watermark so given scheme is non-blind. Peak signal to noise ratio is used to measure the imperceptibility whereas similarity between original and extracted watermark is measured using normalized correlation coefficient. The scheme was tested against various attacks (including histogram equalization, Gaussian noise, cropping, Y-shearing, X-shearing, affine transformation, salt & pepper), to check the robustness. The results of proposed scheme are compared with existing color watermarking schemes. The results show that proposed scheme is robust and imperceptible.
Loudspeakers in portable consumer electronic devices are frequently small in size. Due to the low sensitivity of their drive units, they are pushed to their power handling and mechanical limits by powerful amplifiers ...
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Loudspeakers in portable consumer electronic devices are frequently small in size. Due to the low sensitivity of their drive units, they are pushed to their power handling and mechanical limits by powerful amplifiers in an attempt to reach high volumes. To protect against excessive diaphragm excursions, a model based algorithm is proposed which regulates the voltage input signal to the loudspeaker while minimizing unnecessary system interventions.
In this paper, we proposed a new statistical framework for blind image steganalysis that is shown to be of higher detection performance accuracy than truly current steganalysis systems. Therefore, we have introduced a...
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In this paper, we proposed a new statistical framework for blind image steganalysis that is shown to be of higher detection performance accuracy than truly current steganalysis systems. Therefore, we have introduced a multi-classification methodology based on image features to group images into the optimal classes in order, to make the models specific and differentiated all the infected images. To distinct images more effectively and thus improving the system accuracy, we have applied Gaussian Mixture Model (GMM) and also an unsupervised algorithm to learn a finite mixture model. Afterward, for each images class we can select and design a specific model of steganalyzer. We have also employed Support Vector Machines (SVMs) to design the models of steganalyzer. Proposed framework can enable us to employ multivariate features extracted from different domains in order, to obtain much better distinction of images and also better designing the steganalyzers in which, can be applied to any types of steganalysis techniques. The result comparison shows the advantages of the proposed framework over the current and prior steganalysis systems with the best overall results.
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