To solve the problem that complex radar emitter signals are difficult to identify under low signal-to-noise ratio, this paper proposes a novel radar signal recognition method based on an improved ...deep residual network. In this method, two IQ signals are used as the input of the method, which saves time for generating time-frequency images, and then the signal features are extracted through an improved deep residual network. A nonlinear transform layer is inserted into the network to automatically confirm the threshold value, and then the soft threshold method is used to denoise. The importance of features is weighted by attention unit, and then classified by softmax classifier. The experiments based on five kinds of radar signal datasets show higher accuracy at low signal-to-noise ratio compared with other methods. The experiments also verified its overall accuracy can still exceed 90% even at extremely low signal-to-noise ratio of -16dB.
In order to improve the robustness of existing reversible watermarking algorithms and strengthen the imperceptibility of watermarked images, a robust reversible watermarking algorithm based on ...redundant integer wavelet transform and compressed sensing is proposed. Firstly, the algorithm selects the high capacity embedding regions in the original image and then redundant integer wavelet transform is conducted within the selected areas, and wavelet coefficients matrices are obtained after the sparse. After that, the two intermediate-frequency parts of each wavelet coefficient matrix are conducted by compressed sensing with the same observation matrix, and the two generated compressed observation values are merged. Finally, the watermark is embedded into the observation value of intermediate-frequency coefficient part, to recover the sparse signal by using the reconstruction algorithm, and then the watermarked image is obtained through the redundant integer wavelet inverse transform. Simulation results indicate that the algorithm can not only realize blind extraction, but also significantly improve robustness, imperceptibility and embedded watermark capacity compared with other similar algorithms. It is easy to implement. What’s more, the generated watermarked images have high quality and can completely lossless restore the original carrier image without any attacks.
Semisupervised DR techniques using virtual label regression have attracted considerable attention, but they suffer from two restrictions: the number of discriminant directions available is ...constrained to the number of classes, and they're nonorthogonal. Traditional methods easily address these problems. However, an interesting problem is how to address these restrictions in label regression modelings. To do this, the authors developed Recursive Orthogonal Label Regression (ROLR), a regression framework of semisupervised dimension reduction that uses label propagation and label regression in a recursive procedure. Here, they illustrate the formulation of ROLR using semisupervised regression encoding. ROLR provides an unified view to understand and explain a large family of label regression techniques. Experimental results show the approach's feasibility and effectiveness.
For compressive tracking (CT) algorithm, it is vulnerable to the occlusion, when tracking targets. An improved CT algorithm based on target division and feature point matching is proposed in this ...paper, which can determine different target tracking states by the method of target division. When the target is in normal tracking or partial occlusion, the target is located accurately by the sub-block with the highest discrimination degree. In this scenario, the classifier only updates the unblocked sub regions in order to avoid the error of updating the occlusion information. When the target is completely occluded or lost in some frames, ORB feature matching is used to re-locate the target. Experimental results show that our proposed CT algorithm can improve the robustness of the algorithm and reduces the drift problem.
To improve the visual quality and the embedding rate of the existing reversible image watermarking algorithm, an improved reversible image watermarking algorithm based on difference expansion is ...proposed. First, the watermark information is divided into groups, and the information value of each group is calculated. The watermark group number and the corresponding carrier image block number are mapped, and the corresponding coefficient position of each corresponding carrier block is identified according to the value of the watermark information in each group. Second, the identified location map is compressed and embedded in the original image through the difference expansion. Through circular searching the suitable pixel position, the embedding rate can be effectively improved without sacrificing any visual quality. The experimental results show that the proposed algorithm not only has high embedding rate but also has a high visual quality and can achieve full recovery of the original image. Compared with other algorithms, the algorithm has certain advantages.
The problem of image segmentation has been investigated with a focus on inhomogeneous multiphase image segmentation. Intensity inhomogeneity is an undesired phenomenon that represents the main ...obstacle for magnetic resonance (MR) and natural images segmentation. The complex images usually contain an arbitrary number of objects. This paper presents a new multiphase active contour model method for simultaneous regions classification of MR images and natural images without bias field correction. In this model, a simple and effective initialization method is taken to speed up the curve evolution toward final results; a new multiphase level set method is proposed to segment the multiple regions. This model not only extracts multiple objects simultaneously, but also provides smooth and accurate boundaries of the objects. The results for experiments on several synthetic and real images demonstrate the effectiveness and accuracy of our model.
In order to improve the embedding rate of reversible watermarking algorithm for digital image and enhance the imperceptibility of the watermarked image, an adaptive reversible image watermarking ...algorithm based on DE is proposed. By analyzing the traditional DE algorithm and the generalized DE algorithm, an improved difference expansion algorithm is proposed. Through the analysis of image texture features, the improved algorithm is used for embedding and extracting the watermark. At the same time, in order to improve the embedding capacity and visual quality, the improved algorithm is optimized in this paper. Simulation results show that the proposed algorithm can not only achieve the blind extraction, but also significantly heighten the embedded capacity and non-perception.
Moreover, compared with similar algorithms, it is easy to implement, and the quality of the watermarked images is high. KCI Citation Count: 2
Natural image segmentation is often a crucial first step for high-level image understanding, significantly reducing the complexity of content analysis of images. LRAC may have some disadvantages. (1) ...Segmentation results heavily depend on the initial contour selection which is a very skillful task. (2) In some situations, manual interactions are infeasible. To overcome these shortcomings, we propose a novel model for unsupervised segmentation of viewer’s attention object from natural images based on localizing region-based active model (LRAC). With aid of the color boosting Harris detector and the core saliency map, we get the salient object edge points. Then, these points are employed as the seeds of initial convex hull. Finally, this convex hull is improved by the edge-preserving filter to generate the initial contour for our automatic object segmentation system. In contrast with localizing region-based active contours that require considerable user interaction, the proposed method does not require it; that is, the segmentation task is fulfilled in a fully automatic manner. Extensive experiments results on a large variety of natural images demonstrate that our algorithm consistently outperforms the popular existing salient object segmentation methods, yielding higher precision and better recall rates. Our framework can reliably and automatically extract the object contour from the complex background.
In order to improve the embedding rate of reversible watermarking algorithm for digital image and enhance the imperceptibility of the watermarked image, an adaptive reversible image watermarking ...algorithm based on DE is proposed. By analyzing the traditional DE algorithm and the generalized DE algorithm, an improved difference expansion algorithm is proposed. Through the analysis of image texture features, the improved algorithm is used for embedding and extracting the watermark. At the same time, in order to improve the embedding capacity and visual quality, the improved algorithm is optimized in this paper. Simulation results show that the proposed algorithm can not only achieve the blind extraction, but also significantly heighten the embedded capacity and non-perception. Moreover, compared with similar algorithms, it is easy to implement, and the quality of the watermarked images is high.
This paper studies several kinds of image segmentation algorithm,and region-growing algorithm and fast level set matching algorithm FM are programmed by VC and verified,thereinto,the speed of ...segmentation of region-growing algorithm is fast.It is primarily affected by the identity of gray level of object region, for the inconsistent object region, excessive segmentation and missing segmentation will happen.The fast matching method can easily handle the geometric objects which topological structure is complex or changing, but the evolving curve also easily leak from the boundary, if there are holes in an object which has been segmented, it will not quite separate the interior outline of the object,so,aiming at the characteristics of medical image,an improved fast matching algorithm is presented in this paper, it can effectively enhance the image segmentation effect and prevent the loss of details of lines, and the internal change of topological structures of the objects can also be segmented better by it.
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