CN107240127A - The image registration appraisal procedure of distinguished point based mapping - Google Patents
The image registration appraisal procedure of distinguished point based mapping Download PDFInfo
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- CN107240127A CN107240127A CN201710255374.1A CN201710255374A CN107240127A CN 107240127 A CN107240127 A CN 107240127A CN 201710255374 A CN201710255374 A CN 201710255374A CN 107240127 A CN107240127 A CN 107240127A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
- G06T7/33—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
- G06T7/337—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods involving reference images or patches
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
- G06F18/232—Non-hierarchical techniques
- G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
- G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
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Abstract
The invention discloses a kind of image registration accuracy appraisal procedure of distinguished point based mapping, comprise the steps of：1) some characteristic points of reference picture and image subject to registration are automatically extracted；2) select suitable geometric space transformation model to calculate transformation matrix, complete the registration of reference picture and image subject to registration；3) characteristic point of images after registration is mapped on reference picture；4) the distance between the characteristic point being mapped on reference picture and the characteristic point extracted from reference picture error are counted；5) the distance between characteristic point error is analyzed by K means clustering methods, calculates the registration error of image.The method that the present invention is provided can effectively assess the precision of image registration, help researcher targetedly to reduce data error, and innovatory algorithm performance improves image registration accuracy, to obtain high-definition picture.
Description
Technical field
The invention belongs to digital image processing techniques field, it is adaptable to the qualitative assessment of image registration effect.
Background technology
In image processing field, the judge for processing result image is often leading using the subjective assessment of people, is seen
The influence of the person's of examining subjective factor is larger, it is sometimes desirable to coordinate subjective assessment with objective quantizating index.
It is an important content in image registration field to the qualitative assessment of registration effect.Real image registration is usually
Due to not accurate criterion, considerable assessment can not be obtained by causing the validity of algorithm, so as to influence at follow-up image
Reason analysis and effect.
Registration accuracy is an important indicator of image registration, generally in units of pixel, is reflected between registering image
The uniformity of deformation, directly affects the treatment effects such as follow-up image co-registration, splicing, and target identification.Due to exist translation,
Tend not to realize complete accuracy registration between image and reference picture after the deformation such as scaling, rotation, registration, but have one
Fixed error, trueness error is smaller, shows that the location of pixels in registration result estimates, registration effect more consistent with reference picture
Better；Vice versa.
The content of the invention
The goal of the invention of the present invention is to propose a kind of image registration accuracy appraisal procedure of distinguished point based mapping, is somebody's turn to do
The distance between characteristic point and reference picture characteristic point of the method by calculating images after registration error, objective judgement image registration
Effect.
The goal of the invention of the present invention is achieved through the following technical solutions：
A kind of image registration accuracy appraisal procedure of distinguished point based mapping, is comprised the steps of：
Step 1) automatically extract some characteristic points of reference picture and image subject to registration；
Step 2) select suitable geometric space transformation model to calculate transformation matrix, complete reference picture and figure subject to registration
The registration of picture；
Step 3) utilize step 2) used in transformation matrix the characteristic point of images after registration is mapped on reference picture；
Step 4) statistics the characteristic point being mapped on reference picture and the characteristic point extracted from reference picture between away from
From error；
Step 5) setting error threshold, the distance between characteristic point error is divided into two by K-means clustering methods
Cluster, (1) is if the range error of two cluster centres is above error threshold, then it is assumed that registration failure；(2) if in two clusters
The range error of the heart is both less than error threshold, then it is assumed that all Characteristic points match successes, takes the range error of two cluster centres
Average value be used as Images Registration；(3) if the range error of a cluster centre is more than error threshold, and another is clustered
The range error at center is less than error threshold, then it is assumed that the larger characteristic point of range error belongs to error hiding characteristic point, takes smaller
Range error be used as Images Registration.
The beneficial effects of the present invention are：The method that the present invention is provided can effectively assess the precision of image registration, help
Researcher targetedly reduces data error, and innovatory algorithm performance improves image registration accuracy, to obtain high resolution graphics
Picture；Simultaneously as this method uses the registration Algorithm based on Automatic Feature Extraction, it is to avoid the interference of artificial reconnaissance and limitation,
Also contribute to improve the operation efficiency of algorithm for checking aspect, reached the purpose for improving discrimination and accuracy, permitted
It is significant in many practical applications.
Brief description of the drawings
Fig. 1 is the schematic flow sheet for the image registration accuracy appraisal procedure that distinguished point based maps.
Embodiment
The present invention is described in further detail with reference to the accompanying drawings and examples.
As shown in figure 1, a kind of image registration accuracy appraisal procedure of distinguished point based mapping is by calculating shown in the present embodiment
Machine program realizes that main contents are as follows：
Step 1) characteristic point that completes reference picture and image subject to registration automatically extracts；
Step 2) transformation matrix is calculated according to the suitable geometric space transformation model of image-forming condition selection, complete subject to registration
The spatial registration of image and reference picture；
Step 3) utilize step 2) in transformation matrix the characteristic point of the image after registration is mapped in reference picture；
Step 4) characteristic point that is mapped on reference picture of statistics and step 1) in the characteristic point extracted on reference picture it
Between range error (unit：Pixel)；
Step 5) step-up error threshold value T1, error threshold T1Selection and reference picture and image subject to registration resolution ratio, figure
As registration accuracy requires relevant, it can be set according to actual conditions, usual registration accuracy error is 1~2 pixel.Utilize K-
Means clustering methods, are divided into two clusters by the distance between all characteristic points error, and respectively in the cluster of two clusters
The range error ε of the heart1、ε2Carry out analysis judgement：(1) if the range error ε of two cluster centres1、ε2Above error threshold T1,
Then think that it fails to match；(2) if the range error ε of two cluster centres1、ε2Both less than error threshold T1, then it is assumed that all features
Point matching success, registration error takes the two average value(3) if the range error ε of a cluster centre1It is more than
Error threshold T1, and the range error ε of another cluster centre2Less than error threshold T1, then it is assumed that the larger feature of range error
Point ε1Belong to error hiding characteristic point, do not pay attention to, take less range error as Images Registration, i.e. ε=ε2。
It is understood that for those of ordinary skills, can be with technique according to the invention scheme and its hair
Bright design is subject to equivalent substitution or change, and all these changes or replacement should all belong to the guarantor of appended claims of the invention
Protect scope.
Claims (1)
1. a kind of image registration accuracy appraisal procedure of distinguished point based mapping, is comprised the steps of：
Step 1) automatically extract some characteristic points of reference picture and image subject to registration；
Step 2) the suitable geometric space transformation model of selection calculates transformation matrix, completes reference picture and image subject to registration
Registration；
Step 3) utilize step 2) used in transformation matrix the characteristic point of images after registration is mapped on reference picture；
Step 4) count the distance between the characteristic point being mapped on reference picture and the characteristic point extracted from reference picture by mistake
Difference；
Step 5) setting error threshold, the distance between characteristic point error is divided into by two clusters by K-means clustering methods,
(1) if the range error of two cluster centres is above error threshold, then it is assumed that registration failure；(2) if two cluster centres
Range error is both less than error threshold, then it is assumed that the success of all Characteristic points matchs, take two cluster centres range error it is flat
Average is used as Images Registration；(3) if the range error of a cluster centre is more than error threshold, and another cluster centre
Range error be less than error threshold, then it is assumed that the larger characteristic point of range error belongs to error hiding characteristic point, take it is less away from
Images Registration is used as from error.
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| CN112329848A (en) * | 2020-11-04 | 2021-02-05 | 昆明理工大学 | Image space mapping method based on advection vector field clustering |
| CN113741682A (en) * | 2020-05-29 | 2021-12-03 | 北京七鑫易维信息技术有限公司 | Method, device and equipment for mapping fixation point and storage medium |
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Application publication date: 20171010 |