Disparity map quality evaluation method
A technology of quality assessment and disparity map, applied in the fields of binocular vision and computer vision, which can solve problems such as quality prediction errors
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[0007] specific implementation
[0008] In order to solve the above-mentioned main difficulties, the self-judgment of the depth image is firstly carried out by using the no-reference method, and the corresponding depth of each pixel is obtained according to the results of binocular matching and cost aggregation. , you can judge by yourself according to the following formula
[0009]
[0010] where i is , D is the parallax range, and Respectively in the pixel point p The minimum and maximum value of the cost value, T is the maximum and minimum value threshold. When an object approaches or an occluder appears, Costs with values in all disparity ranges will have very small mutations, and their minimum values will be much smaller than other disparity ranges, at which point their disparity will become very unreliable. When there is no obvious texture or white area in the grayscale image, when the cost value in all parallax ranges fluctuates up and down, and T...
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