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This paper proposes a measurement-based method to estimate application (APP) specific EMI on a device running a time-sharing multi-tasking operating system (OS). The proposed method includes a near-field measurement technique for APP-specific EMI and an algorithm which can estimate system EMI with any different APPs execution sequences. Because of the task-scheduling feature, the execution order of...
Noise estimation is crucial in many image processing algorithms such as image denoising. Conventionally, the noise is assumed as signal-independent additive white Gaussian process. However, for the real raw-data of imaging sensors, the present noise is better modeled as signal-dependent noise. In this work, we propose an efficient image sensor noise estimation method based on iterative re-weighted...
Noise level estimation is crucial in many image processing applications, such as blind image denoising. In this paper, we propose a novel noise level estimation approach for natural images by jointly exploiting the piecewise stationarity and a regular property of the kurtosis in bandpass domains. We design a $K$ -means-based algorithm to adaptively partition an image into a series of non-overlapping...
Superpixel algorithm aims to semantically group neighboring pixels into a coherent region. It could significantly boost the performance of the subsequent vision processing task such as image segmentation. Recently, the work simple linear iterative clustering (SLIC) [1] has drawn huge attention for its state-of-the-art segmentation performance and high computational efficiency. However, the performance...
Noise level estimation is crucial in many image processing applications such as blind image denoising. In this work, we propose a novel noise level estimation approach for natural images by jointly exploiting the piecewise stationarity and a regular property of the kurtosis in band-pass domains. We design a K-means based algorithm to adaptively partition an image into a series of non-overlapping regions,...
Dynamic histogram shifting (DHS) is a generation of the conventional histogram shifting (HS) technique for reversible image watermarking. Its superior embedding performance is achieved at the cost of significantly increased computational burden incurred by estimating the capacity parameters via multi-rounds of embedding iterations. In this work, we propose an analytical framework on estimating the...
A new UKF based for radar and infrared sensor registration method is provided. A so-called "hybrid states" concept is introduced to describe target's state, which consists of the target's range, bearing and elevation and its velocity in the Cartesian coordinate system. The dynamic function and the measurement function are deduced in hybrid states. Simulation results show that the proposed...
In order to compress calculation, the background estimation algorithm for the infrared target detection was proposed. Firstly, a Least Square Matrix is proposed and an image background is estimated. Then the target is detected by self-adaptive threshold detection in different images. It is shown by nonlinear function regression experiment and sequence infrared image detection experiment whose methods...
This paper presents a new technique for high resolution direction finding that only requires the array outputs to be sampled one at a time by a single channel receiver. According to single channel output, we establish a new processing model. The new model is structurally similar to the conventional multiple channel model and the only difference is that the rectification item can be modified. This...
As the huge amount of XML data emerging in Web, researchers begin to focus on the topic of querying against XML data efficiently. Different from the query processing in relational data, XML query is characterized by structural join. Hence, quickly evaluating the cost of the join operation with the size of the intermediate results is an important part of XML query plan generation .In this paper, an...
In this paper, a new Bayesian array signal model structure based on signal reconstruction is proposed, that allows us to define a posterior distribution on the parameter space, which is applicable to both wideband and narrowband signals. Unfortunately, a direct evaluation of this distribution and of its features, including posterior model probabilities, requires evaluation of some complicated high-dimensional...
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