Imaging system and method

Abstract

A method of distance measuring includes obtaining a depth map and a stereo pair of images of a scene of interest, and enhancing a precision of the depth map based on disparity values of corresponding points between the images. The images have a higher resolution than the depth map. Enhancing the precision of the depth map includes optimizing an energy function of the images over a predetermined range of disparity values to obtain an optimized energy function; determining the disparity values based on the optimized energy function; and replacing low precision values of the depth map with corresponding high precision values based on the disparity values.

What is claimed is: 
     
         1 . A method of distance measuring, comprising:
 obtaining a depth map and a stereo pair of images of a scene of interest, the images having a higher resolution than the depth map; and   enhancing a precision of the depth map based on disparity values of corresponding points between the images, including:
 optimizing an energy function of the images over a predetermined range of disparity values to obtain an optimized energy function; 
 determining the disparity values based on the optimized energy function; and 
 replacing low precision values of the depth map with corresponding high precision values based on the disparity values. 
   
     
     
         2 . The method of  claim 1 , wherein optimizing the energy function over the predetermined range of disparity values includes optimizing the energy function over a range of disparity values within a predetermined disparity threshold. 
     
     
         3 . The method of  claim 2 , wherein the predetermined disparity threshold corresponds to a predetermined threshold distance. 
     
     
         4 . The method of  claim 1 , wherein optimizing the energy function over the predetermined range of disparity values includes determining a similarity component of the energy function over the predetermined range of disparity values, the similarity component reflecting correspondences between pixel intensities of the images. 
     
     
         5 . The method of  claim 4 , wherein determining the similarity component includes determining a sum of absolute differences of a pixel dissimilarity metric. 
     
     
         6 . The method of  claim 5 , wherein determining the sum of the absolute differences of the pixel dissimilarity metric includes determining a sum of absolute differences of a Birchfield-Tomasi pixel dissimilarity metric. 
     
     
         7 . The method of  claim 1 , wherein optimizing the energy function includes determining a smoothness component of the energy function reflecting continuity of depth values within the depth map. 
     
     
         8 . The method of  claim 7 , wherein the smoothness component is a weighted sum of trigger functions. 
     
     
         9 . The method of  claim 8 , wherein each of the trigger functions is a function of a disparity difference between a disparity value corresponding to a pixel within the depth map and a disparity value corresponding to one of a plurality of neighboring pixels of the pixel within the depth map. 
     
     
         10 . The method of  claim 9 , wherein a first weight is applied to one or more of the trigger functions of disparity differences that are equal to a non-zero threshold, and a second weight is applied to another one or more of the trigger functions of disparity differences that are larger than the non-zero threshold. 
     
     
         11 . The method of  claim 1 , wherein optimizing the energy function includes optimizing the energy function using at least one of dynamic programming or non-local optimization. 
     
     
         12 . The method of  claim 11 , wherein optimizing the energy function includes optimizing the energy function using recursive filtering. 
     
     
         13 . The method of  claim 1 , wherein replacing the low precision values of the depth map with the corresponding high precision values includes:
 replacing all low precision values of the depth map with corresponding high precision values.   
     
     
         14 . The method of  claim 1 , wherein replacing the low precision values of the depth map with the corresponding high precision values includes:
 replacing selected low precision values of the depth map with corresponding high precision values based on the low precision values being within a predetermined threshold disparity.   
     
     
         15 . The method of  claim 1 , wherein replacing the low precision values of the depth map with the corresponding high precision values includes:
 replacing selected low precision values of the depth map with corresponding high precision values based on the low precision values being within a disparity range that corresponds to a predetermined threshold distance.   
     
     
         16 . The method of  claim 1 , wherein:
 the stereo pair of images are a first stereo pair of images of the scene of interest; and   obtaining the depth map includes obtaining the depth map from a second stereo pair of images of the scene of interest, the second stereo pair of images having a same resolution as the depth map.   
     
     
         17 . The method of  claim 16 , wherein:
 the depth map is a first depth map; and   obtaining the first depth map includes obtaining the first depth map from the second stereo pair of images and a second depth map having a lower resolution than the second stereo pair of images.   
     
     
         18 . The method of  claim 1 , further comprising:
 rectifying the stereo pair of images prior to enhancing the precision of the depth map.   
     
     
         19 . An imaging system, comprising:
 a pair of imaging devices configured to obtain a stereo pair of images of a scene of interest; and   one or more processors configured to enhance a precision of a depth map of the scene of interest based on disparity values of corresponding points between the images, the images having a higher resolution than the depth map, and enhancing the precision of the depth map includes:
 optimizing an energy function of the images over a predetermined range of disparity values to obtain an optimized energy function; 
 determining the disparity values based on the optimized energy function; and 
 replacing low precision values of the depth map with corresponding high precision values based on the disparity values. 
   
     
     
         20 . A non-transitory computer readable storage medium, comprising:
 instruction for obtaining a depth map and a stereo pair of images of a scene of interest, the images having a higher resolution than the depth map; and   instruction for enhancing a precision of the depth map based on disparity values of corresponding points between the images, including:
 instruction for optimizing an energy function of the images over a predetermined range of disparity values to obtain an optimized energy function; 
 instruction for determining the disparity values based on the optimized energy function; and 
 instruction for replacing low precision values of the depth map with corresponding high precision values based on the disparity values.