Image processing method, device and photographic apparatus

Abstract

An image processing method includes correcting a target image based on an initial distortion coefficient to obtain a first corrected target image, performing straight-line fitting on a first border line in the first corrected target image to calculate a first distortion metric value and a correction distortion coefficient, correcting the target image based on the correction distortion coefficient to obtain a second corrected target image, removing outlier points on a second border line in the second corrected target image, performing straight-line fitting on the second border line with the outlier points removed to calculate a second distortion metric value, detecting whether a preset correction condition is satisfied based on at least one of the first distortion metric value or the second distortion metric value, and, if the preset correction condition is satisfied, applying the correction distortion coefficient to subsequent image correction to obtain better corrected images.

What is claimed is: 
     
         1 . An image processing method comprising:
 correcting a target image based on an initial distortion coefficient to obtain a first corrected target image;   performing straight-line fitting on a first border line in the first corrected target image to calculate a first distortion metric value and a correction distortion coefficient;   correcting the target image based on the correction distortion coefficient to obtain a second corrected target image;   removing outlier points on a second border line in the second corrected target image;   performing straight-line fitting on the second border line with the outlier points removed to calculate a second distortion metric value;   detecting whether a preset correction condition is satisfied based on at least one of the first distortion metric value or the second distortion metric value; and   applying, if the preset correction condition is satisfied, the correction distortion coefficient to subsequent image correction to obtain better corrected images.   
     
     
         2 . The method according to  claim 1 , further comprising, before correcting the target image:
 capturing an image of an object including straight line features; and   using the captured image as the target image or adjusting a size of the captured image to obtain the target image.   
     
     
         3 . The method according to  claim 2 , wherein capturing the image of the object including straight line features includes:
 capturing a plurality of images; and   analyzing the plurality of images to determine the image of the object including straight line features.   
     
     
         4 . The method according to  claim 3 , wherein analyzing the plurality of images includes analyzing the plurality of images at a same time using a same processing method. 
     
     
         5 . The method according to  claim 2 , wherein adjusting the size of the captured image includes:
 magnifying, if the size of the captured image is smaller than a preset size threshold, the captured image to a target size through interpolation; or   scaling down, if the size of the captured image is greater than the preset size threshold, the captured image to the target size through down-sampling.   
     
     
         6 . The method according to  claim 1 , wherein performing straight-line fitting on the first border line to calculate the first distortion metric value and the correction distortion coefficient includes:
 performing edge detection on the first corrected target image to determine the first border line in the first corrected target image;   performing straight-line fitting on the first border line based on polynomial straight-line fitting to obtain a fitted straight line; and   calculating the first distortion metric value of the first border line relative to the fitted straight line and the correction distortion coefficient corresponding to the first distortion metric value.   
     
     
         7 . The method according to  claim 6 , wherein calculating the first distortion metric value and the correction distortion coefficient includes:
 determining a straight line segment in the first border line;   calculating distances from corresponding points on the straight line segment to the fitted straight line;   obtaining the first distortion metric value according to the distances; and   performing non-linear optimization on the first distortion metric value to obtain the correction distortion coefficient.   
     
     
         8 . The method according to  claim 1 , wherein:
 correcting the target image according to the initial distortion coefficient includes correcting a target border line in the target image based on the initial distortion coefficient, and   correcting the target image based on the correction distortion coefficient includes correcting the target border line in the target image based on the correction distortion coefficient.   
     
     
         9 . The method according to  claim 1 , wherein performing straight-line fitting on the second border line with the outlier points removed to calculate the second distortion metric value includes:
 performing edge detection on the second corrected target image to determine the second border line in the second corrected target image;   performing straight-line fitting on the second border line based on polynomial straight-line fitting to obtain a fitted straight line; and   calculating the second distortion metric value of the second border line relative to the fitted straight line.   
     
     
         10 . The method according to  claim 9 , wherein calculating the second distortion metric value includes:
 determining a straight line segment in the second border line with the outlier points removed;   calculating distances from corresponding points on the straight line segment to the fitted straight line; and   obtaining the second distortion metric value according to the distances.   
     
     
         11 . The method according to  claim 1 , wherein detecting whether the preset correction condition is satisfied includes:
 calculating a relative variation amount between the first distortion metric value and the second distortion metric value; and   determining whether the relative variation amount calculated is smaller than a preset variation threshold to determine whether the preset correction condition is satisfied.   
     
     
         12 . The method according to  claim 1 , wherein detecting whether the preset correction condition is satisfied includes determining whether the second distortion metric value is smaller than a preset metric threshold. 
     
     
         13 . The method according to  claim 1 , further comprising:
 configuring, if the preset correction condition is not satisfied, the correction distortion coefficient as the initial distortion coefficient.   
     
     
         14 . A camera comprising:
 a camera lens; and   an image processor configured to:
 correct a target image based on an initial distortion coefficient to obtain a first corrected target image; 
 perform straight-line fitting on a first border line in the first corrected target image to calculate a first distortion metric value and a correction distortion coefficient; 
 correct the target image based on the correction distortion coefficient to obtain a second corrected target image; 
 remove outlier points on a second border line in the second corrected target image; 
 perform straight-line fitting on the second border line with the outlier points removed to calculate a second distortion metric value; 
 detect whether a preset correction condition is satisfied based on at least one of the first distortion metric value or the second distortion metric value; and 
 apply, if the preset correction condition is satisfied, the correction distortion coefficient to subsequent image correction to obtain better corrected images. 
   
     
     
         15 . The camera according to  claim 14 , wherein the image processor is further configured to:
 capture an image of an object including straight line features through the camera lens; and   determine the captured image as the target image or adjust a size of the captured image to obtain the target image.   
     
     
         16 . The camera according to  claim 15 , wherein the image processor is further configured to:
 capture a plurality of images; and   analyze the plurality of images to determine the image of the object including straight line features.   
     
     
         17 . The camera according to  claim 15 , wherein the image processor is further configured to analyze the plurality of images at a same time using a same processing method. 
     
     
         18 . The camera according to  claim 15 , wherein the image processor is further configured to:
 magnify, if the size of the captured image is smaller than a preset size threshold, the captured image to a target size through interpolation; or   scale down, if the size of the captured image is greater than the preset size threshold, the captured image to the target size through down-sampling.   
     
     
         19 . The camera according to  claim 14 , wherein the image processor is further configured to:
 perform edge detection on the second corrected target image to determine the second border line in the second corrected target image;   perform straight-line fitting on the second border line based on polynomial straight-line fitting to obtain a fitted straight line; and   calculate the second distortion metric value of the second border line relative to the fitted straight line.   
     
     
         20 . The camera according to  claim 19 , wherein the image processor is further configured to:
 determine a straight line segment in the second border line with the outlier points removed;   calculate distances from corresponding points on the straight line segment to the fitted straight line; and   obtain the second distortion metric value according to the distances.