图像深度获取是机器视觉领域活跃的研究课题。将图像深度估计问题归结为模式识别问题,以单目图像深度为待分连续模式类,在多尺度下对图像块提取绝对和相对深度特征,选择表征上下文关系的MRF(Markov Random Field)-MAP(Maximum a posteriori)方法,建立拉普拉斯模型,表述某图像块的深度和其邻域深度之间的关系。实验得到了某一类单目图像对应的深度图像,证明了该算法的有效性。
Depth perception for night vision （NV） imagery could largely improve scene comprehension. We present a novel scheme to give fused multi-band NV imagery smoothly natural color appearance as well as depth sense from color. Our approach is based on simulating color cues by varying saturation values of each object in the color NV image, in correspondence with the ratio between the infrared and low-light-level sensor outputs which in practice is the depth feature for same materials. We render the NV image segment- by-segment by taking advantage image fusion. Experiments have of image segmentation, dominant shown that the proposed scheme color transfer, saturation variation, and can achieve satisfying results.
