Image splicing method and apparatus
An image stitching and image technology, applied in image data processing, graphic image conversion, instruments, etc., can solve problems such as inability to apply to most users of mobile terminals, large changes in shooting angles, and complex calculation methods.
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Example Embodiment
[0057] Reference figure 1 , Shows Embodiment 1 of an image stitching method of the present invention, which may specifically include:
[0058] Step 101: For the first image and the second image to be spliced, respectively extract the key points of each image and the characteristic parameters of the key points; the first image and the second image may be selected by the user from an image library;
[0059] Step 102: Acquire corresponding key point pairs between the first image and the second image;
[0060] Step 103: Obtain the transformation relationship between the image point position coordinates of the two images according to the key point pair;
[0061] For example, using polynomial fitting regression to obtain the transformation relationship:
[0062] u = a 0 + a 1 ...
Example Embodiment
[0094] Embodiment 1
[0095] The present invention can obtain the corresponding key point pairs between the first image and the second image in the following ways: create a Kd tree according to the key points of the first image and its characteristic parameters; for each key point of the second image, use the most The neighboring point search algorithm obtains the corresponding key points in the first image, and obtains the key point pairs.
[0096] The KD-tree technology used in the present invention has a fast retrieval speed, and its space complexity is in a linear relationship with the dimension of the data set, and it is compatible with the implementation of the secondary memory. Therefore, it is a very effective index algorithm (which can satisfy mobile Real-time requirements of the terminal). Its basic idea is to divide the data set into two sub-data sets according to certain criteria, and then recursively divide the two sub-data sets to form a retrieval tree.
[0097] K ne...
Example Embodiment
[0098] Embodiment 2
[0099] The present invention also obtains the corresponding key point pair between the first image and the second image in the following manner:
[0100] (1) Create a K-d tree based on the key points and characteristic parameters of the first image;
[0101] (2) For each key point of the second image, the nearest neighbor point search algorithm is used to obtain the nearest neighbor key point and the second neighbor key point corresponding to it in the first image;
[0102] (3) Obtain the distance between the key point kp of the second image and the nearest key point kp1 | kp ⇔ kp 1 | , And the distance between the key point kp and the next neighbor key point kp2 | kp ⇔ kp 2 | ;
[0103] (4) Compare the above two distances, and if the preset condit...
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