Lianfa Bai

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Salient object detection remains one of the most important and active research topics in computer vision, with wide-ranging applications to object recognition, scene understanding, image retrieval, context aware image editing, image compression, etc. Most existing methods directly determine salient objects by exploring various salient object features. Here,(More)
The goal of saliency detection is to locate important regions in an image which attract viewers’ attention the most. In this paper, we propose a dynamic Bayesian model for saliency detection in which both Boolean-based and foreground-based models are exploited. First, a preliminary saliency map is constructed based on multi-channel Boolean maps, and a(More)
Sparse and redundant representations perform well in image denoising. However, sparsity-based methods fail to denoise low-light-level (LLL) images because of heavy and complex noise. They consider sparsity on image patches independently and tend to lose the texture structures. To suppress noises and maintain textures simultaneously, it is necessary to embed(More)
In this paper, on the base of analysis on low light level (LLL) image and infrared (IR) thermal image's characteristics, the researches on the processing and fusion on LLL and IR image has been done. The dual-channel image registration techniques of LLL and IR image are put forward, including digital real-time shift technique and dual-channel fusion(More)
In dual-spectrum night vision technology, the fusion image quality is the key to appraise the fusion method The target of dual-spectrum night vision technology is to enhance the definition of the scenery and the target identification probability, according to the above requirement, using the target identification probability, the signal to noise ratio and(More)