Robust focus ranging

Hari N. Nair, C. Stewart
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引用次数: 57

Abstract

Depth maps obtained from focus ranging can have numerous errors and distortions due to edge bleeding, feature shifts, image noise, and field curvature. An improved algorithm that examines an initial high depth-of-field image of the scene to identify regions susceptible to edge bleeding and image noise is given. Focus evaluation windows are adapted to local image content and optimize the tradeoff between spatial resolution and noise sensitivity. An elliptical paraboloid field curvature model is used to reduce range distortion in peripheral image areas. Spatio-temporal tracking compensates for image feature shifts. The result is a sparse but reliable depth map.<>
强大的对焦测距
由于边缘出血、特征移位、图像噪声和视场曲率,从焦点测距获得的深度图可能有许多误差和扭曲。给出了一种改进的算法,该算法通过检查场景的初始高景深图像来识别易受边缘出血和图像噪声影响的区域。焦点评估窗口适应局部图像内容,优化空间分辨率和噪声灵敏度之间的权衡。采用椭圆抛物面场曲率模型来减小外围图像区域的距离畸变。时空跟踪补偿图像的特征移位。结果是一个稀疏但可靠的深度图
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