System and method for splicing images

Patent metadata

Field	Value
Publication number	US-2022392072-A1
Application number	US-202217819925-A
Country	US
Kind code	A1
Filing date	Aug 15, 2022
Priority date	Jul 14, 2016
Publication date	Dec 8, 2022
Grant date	—

Abstract

The present disclosure relates to systems and methods for image splicing. The systems and methods may acquire a first image and a second image, determine a plurality of first feature points in a first region of the first image, determine a plurality of second feature points in a second region of the second image, then match the plurality of first feature points with the plurality of second feature points to generate a plurality of point pairs. Based on the plurality of point pairs, a third region on the first image and a fourth region on the second image may be determined. Finally, a third image may be generated based on the first image and the second image, wherein the third region of the first image may overlap with the fourth region of the second image in the third image.

First claim

We claim:

1 . A method for correcting grayscale of an image implemented on a computing device including at least one processor and a storage, the method comprising:
determining a first region of interest (ROI) in a first image and a second ROI in a second image; determining a first overlapping region of the first image and the second image in the first image and a second overlapping region of the first image and the second image in the second image; determining a first intersection region of the first ROI and the first overlapping region in the first image and a second intersection region of the second ROI and the second overlapping region in the second image; determining the first image as a reference image; determining a first grayscale range of the first intersection region and a second grayscale range of the second intersection region; determining a correction slope based on the first grayscale range and the second grayscale range; and correcting a grayscale of the second ROI in the second image based on the correction slope.

2 . The method of claim 1 , further comprising:
determining an intercept based on a grayscale average of the first intersection region, a grayscale average of the second intersection region, and the correction slope; and correcting the grayscale of the second ROI in the second image based on the correction slope and the intercept.

3 . The method of claim 1 , wherein the first grayscale range is larger than the second grayscale range; and the determining the first image as a reference image includes:
determining the first image including the first intersection region with a larger grayscale range as the reference image.

4 . The method of claim 1 , the determining the first image as a reference image including:
determining a first grayscale range of the first ROI and a second grayscale range of the second ROI, the first grayscale range being larger than the second grayscale range; and determining the first image including the first ROI with a larger grayscale range as the reference image.

5 . The method of claim 1 , further comprising:
determining a first non-ROI region in the first image and a second non-ROI region in the second image; and correcting a grayscale of the second non-ROI region in the second image based on a grayscale of the first non-ROI region in the first image.

6 . The method of claim 5 , the correcting a grayscale of the second non-ROI region in the second image based on a grayscale of the first non-ROI region in the first image further comprising:
correcting the grayscale of the second non-ROI region in the second image based on a grayscale of the first non-ROI region in the first image using a compression curve.

7 . The method of claim 6 , wherein the compression curve includes a compression coefficient and determining the compression coefficient includes:
determining a third intersection region of the first non-ROI region and the first overlapping region in the first image and a fourth intersection region of the second non-ROI region and the second overlapping region in the second image; and determining the compression coefficient based on an average grayscale of the third intersection region and an average grayscale of the fourth intersection region.

8 . The method of claim 1 , further comprising:
splicing the first image and the corrected second image to generate a third image.

9 . The method of claim 8 , further comprising:
dividing the first overlapping region of the first image into a plurality of first sub-regions; dividing the second overlapping region of the corrected second image into a plurality of second sub-regions; matching the plurality of first sub-regions and the plurality of second sub-regions to generate a plurality of sub-region pairs; determining whether the number of the plurality of sub-region pairs is greater than a threshold; and upon the determination that the number of the plurality of sub-region pairs is greater than the threshold, determining that the splicing of the first image and the corrected second image is correct.

10 . The method of claim 9 , wherein the plurality of first sub-regions are non-directly exposure regions in the first overlapping region and the plurality of second sub-regions are non-directly exposure regions in the second overlapping region.

11 . The method of claim 10 , further comprising:
determining an intersection of non-directly exposure regions of the first overlapping region and non-directly exposure regions of the second overlapping region; and determining the plurality of first sub-regions and the plurality of second sub-regions based on the intersection.

12 . A system comprising:
at least one storage including a set of instructions or programs; at least one processor configured to communicate with the at least one storage, wherein when executing the set of instructions or programs, the at least one processor is directed to:
determine a first region of interest (ROI) in a first image and a second ROI in a second image;
determine a first overlapping region of the first image and the second image in the first image and a second overlapping region of the first image and the second image in the second image;
determine a first intersection region of the first ROI and the first overlapping region in the first image and a second intersection region of the second ROI and the second overlapping region in the second image;
determine the first image as a reference image;
determine a first grayscale range of the first intersection region and a second grayscale range of the second intersection region;
determine a correction slope based on the first grayscale range and the second grayscale range; and
correct a grayscale of the second ROI in the second image based on the correction slope.

13 . The system of claim 12 , wherein the at least one processor is further directed to:
determine an intercept based on a grayscale average of the first intersection region, a grayscale average of the second intersection region, and the correction slope; and correct the grayscale of the second ROI in the second image based on the correction slope and the intercept.

14 . The system of claim 12 , wherein the first grayscale range is larger than the second grayscale range; and to determine the first image as the reference image, the at least one processor is further directed to:
determine the first image including the first intersection region with a larger grayscale range as the reference image.

15 . The system of claim 12 , wherein the at least one processor is further directed to:
determine a first non-ROI region in the first image and a second non-ROI region in the second image; and correct a grayscale of the second non-ROI region in the second image based on a grayscale of the first non-ROI region in the first image.

16 . The system of claim 15 , wherein to correct the grayscale of the second non-ROI region in the second image based on the grayscale of the first non-ROI region in the first image, the at least one processor is further directed to:
correct the grayscale of the second non-ROI region in the second image based on a grayscale of the first non-ROI region in the first image using a compression curve.

17 . The system of claim 16 , wherein the compression curve includes a compression coefficient and to determine the compression coefficient, the at least one processor is further directed to:
determine a third intersection region of the first non-ROI region and the first overlapping region in the

Assignees

• Shanghai United Imaging Healthcare Co Ltd

Inventors

• Hu Yang
• Niu Jie
• Xu Liang
• Han Yecheng
• Wang Hanyu
• Bian Yueyan
• Teng Wanli
• Cui Kai
• Yang Le

Classifications

• G06T2207/10081

  Computed x-ray tomography [CT] · CPC title

• G06T7/174

  involving the use of two or more images · CPC title

• G06T7/0014 Primary

  using an image reference approach · CPC title

• G06T7/33 Primary

  using feature-based methods · CPC title

• G06T7/97

  Determining parameters from multiple pictures (depth or shape recovery from multiple images G06T7/55; stereo camera calibration G06T7/85) · CPC title