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Visual saliency detection is a challenging problem in computer vision, but one of great importance and numerous applications. In this paper, we propose a novel model for bottom-up saliency within the Bayesian framework by exploiting low and mid level cues. In contrast to most existing methods that operate directly on low level cues, we propose an algorithm(More)
Image saliency detection is very useful in many computer vision tasks while it still remains a challenging problem. In this paper, we propose a new computational saliency detection model which is implemented with a coarse to fine strategy under the Bayesian framework. First, saliency points are applied to get a coarse location of the saliency region. And(More)
Different power amplifier (PA) models have their own effects on PA linearization. In this paper, the nonlinear characteristic of the radio frequency power amplifier (RF PA) is simulated based on the two models combining predistortion technology, and the nonlinear effects of the two models are analyzed, respectively. The simulation results show that Power(More)
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