CN108234896A - It is segmented exposure image high dynamic restoration methods and system - Google Patents
It is segmented exposure image high dynamic restoration methods and system Download PDFInfo
- Publication number
- CN108234896A CN108234896A CN201810042446.9A CN201810042446A CN108234896A CN 108234896 A CN108234896 A CN 108234896A CN 201810042446 A CN201810042446 A CN 201810042446A CN 108234896 A CN108234896 A CN 108234896A
- Authority
- CN
- China
- Prior art keywords
- exposure
- brightness value
- pixel brightness
- value
- section
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 34
- 230000011218 segmentation Effects 0.000 claims abstract description 29
- 238000011084 recovery Methods 0.000 claims description 20
- 238000013507 mapping Methods 0.000 claims description 10
- 230000006835 compression Effects 0.000 claims description 7
- 238000007906 compression Methods 0.000 claims description 7
- 238000012360 testing method Methods 0.000 claims description 4
- 239000012634 fragment Substances 0.000 claims description 3
- 238000012937 correction Methods 0.000 abstract description 3
- 238000012545 processing Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000005070 sampling Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/70—Circuitry for compensating brightness variation in the scene
- H04N23/73—Circuitry for compensating brightness variation in the scene by influencing the exposure time
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/70—Circuitry for compensating brightness variation in the scene
- H04N23/741—Circuitry for compensating brightness variation in the scene by increasing the dynamic range of the image compared to the dynamic range of the electronic image sensors
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/80—Camera processing pipelines; Components thereof
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
- H04N25/50—Control of the SSIS exposure
- H04N25/53—Control of the integration time
- H04N25/533—Control of the integration time by using differing integration times for different sensor regions
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
- H04N25/50—Control of the SSIS exposure
- H04N25/57—Control of the dynamic range
- H04N25/58—Control of the dynamic range involving two or more exposures
- H04N25/587—Control of the dynamic range involving two or more exposures acquired sequentially, e.g. using the combination of odd and even image fields
- H04N25/589—Control of the dynamic range involving two or more exposures acquired sequentially, e.g. using the combination of odd and even image fields with different integration times, e.g. short and long exposures
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Image Processing (AREA)
- Studio Devices (AREA)
Abstract
The present invention proposes that a kind of segmentation exposure image high dynamic restoration methods and system, this method include the following steps：Each pixel brightness value Vi of section last time of exposure T of the exposure sections of each pixel brightness value V1i and second of section last time of exposure T1 of the first exposure section is obtained, the first exposure section is prior to the second exposure section；Calculate the slope value K of the corresponding current light intensity of each pixel；According to each slope value K and the total exposure time T of two exposure sections, the current pixel brightness value Vxi=K*T of each pixel is calculated；One overexposure comparison range is determined according to the average overexposure value of the first exposure section, judgement is compared to each pixel brightness value V1i and is handled, the high-dynamics image so as to be restored.The segmentation exposure image high dynamic restoration methods and system of the present invention are restored to eliminate the droop that segmentation exposure introduces while high-dynamics image, without additional correction.
Description
Technical field
The present invention relates to technical field of image processing more particularly to a kind of segmentation exposure image high dynamic restoration methods
And system.
Background technology
The Exposure mode of common image sensor is exposed for single hop, and dynamic range is relatively small.There is a kind of image to pass at present
Sensor in a manner that segmentation exposes, is divided to two sections or multistage responds illumination, can improve dynamic range.Referring to figure
1, by taking two exposure as an example, in total exposure time in the range of T ', to be divided into 0-T1 ' and T1 '-T ' two time of integration, the
In one section of exposure period 0-T1 ', saturation value is limited to V1 ' (being limited by manufacture craft), in second segment exposure period
Continue to expose in T1 '-T '.For dim light, within the 0-T1 ' periods, exposure value is there is no saturation value V1 ' is arrived, so entire
It is exposed always in time T ', is exposure value lines b in image；And for strong light, there may be not up in 0-T1 '
T1 ' the moment and exposure value has reached saturation value V1 ', numerical value will not further increase in this section at this time, until in the T1 '-T2 ' times
Inside continue to expose, be exposure value lines a in image.For multistage exposure and in this way, in each segmentation in multistage exposure
It is likely to maintain an equal level a period of time not increased situation there are exposure value before point.Strong light and dim light, can be with by whether can be
It closes at waypoint and exposure value a period of time that maintains an equal level occurs and distinguish.
The mode of such segmentation exposure since centre maintains an equal level section there are exposure value, thus limits certain high dynamic range
It encloses；Due to technological reason, the saturation value V1 ' of each pixel is not completely the same, has deviation, causes under similary light intensity,
After the saturation value V1 ' of each pixel, there are droops for output valve.In addition, the image that this mode acquires, due to using
Linear mode carries out high dynamic compression so that final output dynamic range of images is limited.
Invention content
The technical problems to be solved by the invention are to provide a kind of segmentation exposure image high dynamic restoration methods and system, extensive
The droop that segmentation exposure introduces is eliminated while multiple high-dynamics image, without additional correction.
To solve the above problems, the present invention proposes a kind of segmentation exposure image high dynamic restoration methods, include the following steps：
S1：Obtain the section of the exposure sections of each pixel brightness value Vli and second of section last time of exposure T1 of the first exposure section
Each pixel brightness value Vi of last time of exposure T, i=1~n, n are the quantity of pixel, and the first exposure section is prior to second
Expose section；
S2：The slope value K of the corresponding current light intensity of each pixel is calculated, wherein, K=(Vi-Vli)/(T-T1)；
S3：According to each slope value K and the total exposure time T of two exposure sections, the current pixel of each pixel is calculated
Brightness value Vxi=K*T；
S4：According to first exposure section average overexposure value determine an overexposure comparison range, to each pixel brightness value Vli into
Row multilevel iudge：
If pixel brightness value Vli does not reach the minimum value of the overexposure comparison range, final pixel brightness value Voi=Vi；
If pixel brightness value Vli is more than the maximum value of the overexposure comparison range, final pixel brightness value Voi=Vxi；
If pixel brightness value Vli in the overexposure comparison range, carries out fuzzy Judgment its tendency situation, according to tendency feelings
Condition determines final pixel brightness value Voi=Vi or final pixel brightness value Voi=Vxi.
According to one embodiment of present invention,
When entire exposure image process is divided into two sections, then in the step S1, this two exposure sections, the first exposure are chosen
The section of section last time of exposure T1 is the time of exposure of waypoint, and second exposes section last time of exposure T of section to complete the time of exposure,
Restore to complete after performing step S2-S4；
When exposing number of fragments more than two sections, two exposure sections are chosen from back to front and perform step S1-S4, based on recovery
Pixel brightness value afterwards, move forward one exposure section and choose it is corresponding two exposure section perform step S1-S4, and so on until
All exposure section is restored to complete.
According to one embodiment of present invention, step S5 is further included, by way of gamma mapping curves, will have been restored
The size compression of high-dynamics image after is mapped in the range of the bit wide of output.
According to one embodiment of present invention, in the step S4, the overexposure comparison range is VfA~Vf+A, and Vf is
The average overexposure value of first exposure section, A are luminance deviation value.
According to one embodiment of present invention, the average overexposure value of the first exposure section is obtained for off-line test, brightness
The value range of deviation A is 0~20.
According to one embodiment of present invention, in the step S4, carrying out fuzzy Judgment, it is inclined to situation, according to tendency feelings
Condition determines final pixel brightness value Voi=Vi or final pixel brightness value Voi=Vxi, including：
Centered on the pixels of pixel brightness value Vli in the overexposure comparison range, certain area is chosen；
The regional average value Vm of each pixel brightness value Vi in the region and each current pixel brightness value are calculated respectively
The mean value Vxm of Vxi；
The absolute value of the difference and Vs of each pixel brightness value Vi and its mean value Vxm and each is calculated in the region respectively
The absolute value of the difference and Vxs of current pixel brightness value Vxi and its mean value Vxm；
Judged, if Vxs ＜ Vs, Vo=Vxi, on the contrary Vo=Vi.
According to one embodiment of present invention, selected regional extent is to be compared with pixel brightness value Vli in the overexposure
In the range of the pixel centered on MxN pixel composition region, the equal value of M, the N be 3~5.
According to one embodiment of present invention, pixel brightness value acquired in the step S1 obtains in the following manner
：During exposure image, in the section of the non-final exposure section for the completing exposure last time of exposure, each pixel at the moment is acquired
It is stored after brightness value；And it is bright to acquire each pixel at the moment in the section last time of exposure for the exposure section for being finally completed exposure
After angle value, the pixel brightness value of storage is obtained together, enters step in S2 and performs.
Exposure image high dynamic recovery system is segmented the present invention also provides a kind of, including：
Pixel brightness value acquisition module：Perform each pixel brightness value for section last time of exposure T1 for obtaining the first exposure section
Each pixel brightness value Vi of section last time of exposure T of the exposure sections of Vli and second, i=1~n, n are the quantity of pixel, described
First exposure section is prior to the second exposure section；
Slope value computing module：The slope value K for calculating the corresponding current light intensity of each pixel is performed, wherein, K=(Vi-
Vli)/(T-T1)；
Current pixel brightness value computing module：The total exposure time T according to each slope value K and two exposure sections is performed,
Calculate the current pixel brightness value Vxi=K*T of each pixel；
Recovery module：It performs and an overexposure comparison range is determined according to the average overexposure value of the first exposure section, to each pixel
Brightness value Vli is compared judgement：
If pixel brightness value Vli does not reach the minimum value of the overexposure comparison range, final pixel brightness value Voi=Vi；
If pixel brightness value Vli is more than the maximum value of the overexposure comparison range, final pixel brightness value Voi=Vxi；
If pixel brightness value Vli in the overexposure comparison range, carries out fuzzy Judgment its tendency situation, according to tendency feelings
Condition determines final pixel brightness value Voi=Vi or final pixel brightness value Voi=Vxi.
According to one embodiment of present invention, it further includes：
Curve mapping unit is performed by way of gamma mapping, by the big of the high-dynamics image after the completion of recovery
Small compression is mapped in the range of the bit wide of output.
After adopting the above technical scheme, the present invention has the advantages that compared with prior art：
In the present invention, by the pixel brightness value of the section of the two exposure sections last time of exposure, the processing of linear exposure is carried out,
The current pixel brightness value considered based on linear exposure is obtained, and the pixel of the section for passing through the first exposure section last time of exposure is bright
Angle value judge pixel whether overexposure, and ambiguity is further judged, it is corresponding linear so as to be carried out to overexposure situation
Processing, final pixel brightness value cause high-dynamics image to be restored, simultaneously as the recovery of high-dynamics image also therewith will
The droop that segmentation exposure introduces is to eliminating, without additional correction.
Description of the drawings
Fig. 1 is the exposure lines schematic diagram of current two exposure imaging；
Fig. 2 is the flow diagram of the segmentation exposure image high dynamic restoration methods of one embodiment of the invention；
Fig. 3 is the flow diagram of the segmentation exposure image high dynamic restoration methods of another embodiment of the present invention；
By a pixel centered on the area schematics of institute selection area of the Fig. 4 for one embodiment of the invention.
Specific embodiment
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, below in conjunction with the accompanying drawings to the present invention
Specific embodiment be described in detail.
Many details are elaborated in the following description in order to fully understand the present invention.But the present invention can be with
Much implement different from other manner described here, those skilled in the art can be in the situation without prejudice to intension of the present invention
Under do similar popularization, therefore the present invention is not limited to the specific embodiments disclosed below.
Referring to Fig. 1, in one embodiment, exposure image high dynamic restoration methods are segmented, are included the following steps：
S1：Obtain the section of the exposure sections of each pixel brightness value Vli and second of section last time of exposure T1 of the first exposure section
Each pixel brightness value Vi of last time of exposure T, i=1~n, n are the quantity of pixel, and the first exposure section is prior to second
Expose section；
S2：The slope value K of the corresponding current light intensity of each pixel is calculated, wherein, K=(V-V1)/(T-T1)；
S3：According to each slope value K and the total exposure time T of two exposure sections, the current pixel of each pixel is calculated
Brightness value Vxi=K*T；
S4：According to first exposure section average overexposure value determine an overexposure comparison range, to each pixel brightness value Vli into
Row multilevel iudge：
If pixel brightness value Vli does not reach the minimum value of the overexposure comparison range, final pixel brightness value Voi=Vi；
If pixel brightness value Vli is more than the maximum value of the overexposure comparison range, final pixel brightness value Voi=Vxi；
If pixel brightness value Vli in the overexposure comparison range, carries out fuzzy Judgment its tendency situation, according to tendency feelings
Condition determines final pixel brightness value Voi=Vi or final pixel brightness value Voi=Vxi.
Expansion description is carried out, but should not be with this to the segmentation exposure image high dynamic restoration methods of the embodiment of the present invention below
As limitation.
The segmentation exposure image high dynamic restoration methods of the embodiment of the present invention are applicable to the figure using segmentation Exposure mode
As sensor, point two exposure or (three sections or more) exposures of multistage can be divided into, it is specific unlimited.It can solve segmentation exposure process
The exposure value when closing at waypoint of middle appearance may maintain an equal level a period of time, and the restricted technology of high dynamic range is caused to be asked
Topic so that high-dynamics image is restored.
In step sl, it since this method exposes section unfolding calculation both for two every time, thus first obtains and calculates
The corresponding data of two required exposure sections：Obtain each pixel brightness value Vli of section last time of exposure T1 of the first exposure section
And second exposure section section last time of exposure T each pixel brightness value Vi, i=1~n, n are the quantity of pixel.
The first exposure section is prior to the second exposure section.Such as in the case where entire exposure process is divided into two sections,
0-T1 is the first exposure section, and T1-T is the second exposure section, and total exposure time T, overall exposing is completed under moment T.And whole
In the case that a exposure process is divided into multistage, T1-T is still the second exposure section, and the first exposure Duan Ze is according to waypoint T1 and preceding
One waypoint moment determines.
Each pixel brightness value Vli and each pixel brightness value Vi can be stored first after collection, Ran Houbu
Corresponding data can be obtained from memory, and then enter in follow-up step and calculated in rapid S1.
Preferably, pixel brightness value acquired in the step S1 obtains in the following manner：During exposure image,
In the section of the non-final exposure section for the completing exposure last time of exposure, stored after acquiring each pixel brightness value at the moment；
And after acquiring each pixel brightness value at the moment in the section last time of exposure for the exposure section for being finally completed exposure, it obtains deposit together
The pixel brightness value of storage, enters step in S2 and performs.RAM can be stored in, and (random access memory, arbitrary access are deposited
Reservoir) in.By the first storage first sampled, and calculating is just directly entered when the data sampling that the moment is completed in exposure is completed, it can
To reduce read-write consumption, speed up processing promotes the real-time that high-dynamics image restores.
For example, in the case where exposure section is two sections, in exposure process, when the section last time of exposure to the first exposure section
During T1, each pixel brightness value Vli at the moment is acquired, and is stored in memory, and when the section to the second exposure section
During last time of exposure T, each pixel brightness value Vi at the moment is acquired, and by each pixel brightness value Vli mono- from memory
And it obtains and out enters step S2 execution.Certainly, in the case where exposure section is multistage, former sections of the last time of exposure acquisition of section
Pixel brightness value all stored, until the section of the final stage last time of exposure acquired after the leading portion of acquisition successively pixel
Brightness value enters step S2 execution.
Then step S2 is performed, for each pixel Vi at T moment, it is corresponding the T1 moment can be read from memory
The pixel value Vli of pixel the considerations of for linear exposure, can calculate the slope value of the corresponding current light intensity of each pixel
K, wherein, K=(Vi-Vli)/(T-T1).During this, each pixel of entire image can be directed to by way of traversal
It is calculated, obtains the current light intensity slope value of each pixel.
Then step S3 is performed, according to each slope value K and the total exposure time T of two exposure sections, calculates each pixel
The current pixel brightness value Vxi=K*T of point.These current pixel brightness values Vxi is determining based on linear exposure, thus such as
It, can be by current pixel brightness value Vxi come to this saturation feelings when exposure value saturation occurs at strong light, waypoint in fruit
Condition is restored, thus requires consideration for how automatic rapidly differentiation saturation and unsaturated situation, and the embodiment of the present invention passes through step
Rapid S4 solves the problems, such as this.
Then step S4 is performed, an overexposure comparison range is determined according to the average overexposure value of the first exposure section, to each picture
Plain brightness value V1i is compared judgement, determines final pixel brightness value according to judging result, overexposure comparison range is its minimum
The interval range that value and maximum value are limited.This judgement is to be directed to each pixel brightness value V1i, thus can traverse these pictures
Plain brightness value V1i is judged and is handled.
If pixel brightness value V1i does not reach the minimum value of the overexposure comparison range, final pixel brightness value Voi=Vi；
Pixel brightness value V1i is less than the minimum value of overexposure comparison range, illustrates that overexposure does not occur in it, nor non-linear value, thus
Final pixel brightness value can be set as to the pixel brightness value Vi that the sampling of moment T is completed in exposure.
If pixel brightness value V1i is more than the maximum value of the overexposure comparison range, final pixel brightness value Voi=Vxi；Picture
Plain brightness value V1i be less than overexposure comparison range maximum value, illustrate that overexposure has occurred in it, by final pixel brightness value be set as through
The current pixel brightness value Vxi that linear process is crossed.
If pixel brightness value V1i in the overexposure comparison range, carries out fuzzy Judgment its tendency situation, according to tendency feelings
Condition determines final pixel brightness value Voi=Vi or final pixel brightness value Voi=Vxi.Pixel brightness value V1i is in the overexposure ratio
When compared in the range of, illustrate that its value for non-linear value, needs linearly to be corrected, fuzzy judgement can be carried out to it, if the value is more
Close to linear processed current pixel brightness value Vxi, then final pixel brightness value Voi=Vxi, and if the value closer to
The pixel brightness value Vi of moment T sampling is completed in exposure, then final pixel brightness value Voi=Vi.
In this way, when exposure is divided into two sections, the high-dynamics image after being restored at this time, and expose a point non-multistage
When, then it is the recovery for selected two sections realization high-dynamics images.
Preferably, in the step S4, the overexposure comparison range is Vf A~Vf+A, and Vf is being averaged for the first exposure section
Overexposure value, A are luminance deviation value.That is, the minimum value of overexposure comparison range is Vf A, maximum value is Vf+A.
Optionally, the average overexposure value of the first exposure section is obtained for off-line test, can first be deposited test result
Storage is then obtained and is calculated；The value range of luminance deviation value A is 0~20, this 0~20 is in pixel intensity value 0~255
0~20.
Preferably, in the step S4, carrying out fuzzy Judgment, it is inclined to situation, determines that final pixel is bright according to tendency situation
Angle value Voi=Vi or final pixel brightness value Voi=Vxi, further comprises the steps：
Centered on the pixels of pixel brightness value V1i in the overexposure comparison range, certain area is chosen；
The regional average value Vm of each pixel brightness value Vi in the region and each current pixel brightness value are calculated respectively
The mean value Vxm of Vxi；
(section last time of exposure T of second exposure section) each pixel brightness value Vi and its mean value are calculated in the region respectively
The absolute value of the difference and Vs of Vxm and (calculating each pixel) each current pixel brightness value Vxi and its mean value Vxm
Absolute value of the difference and Vxs；
Judged, if Vxs ＜ Vs, Vo=Vxi, on the contrary Vo=Vi.
Preferably, selected regional extent is the pixel in the overexposure comparison range with pixel brightness value V1i
Centered on MxN pixel composition region, the equal value of M, the N be 3~5.Referring to Fig. 4, P (y, x) is pixel brightness value V1i
The pixel in the overexposure comparison range, M and the equal values of N are 3, three rows, three row pixel using centered on P (y, x) as
Selected region.
When entire exposure image process is divided into two sections, then in the step S1, this two exposure sections (two altogether are chosen
Section is exposed, thus has been performed successively so as to step S1-S4), section last time of exposure T1 of the first exposure section is waypoint
The time of exposure, section last time of exposure T of the second exposure section restore to complete to complete the time of exposure after performing step S2-S4.
When exposing number of fragments more than two sections, two exposure sections are chosen from back to front and perform step S1-S4, based on recovery
Pixel brightness value afterwards, move forward one exposure section and choose it is corresponding two exposure section perform step S1-S4, and so on until
All exposure section is restored to complete.That is, when performing step S1-S4 for the first time, selected two exposure sections are exposures
Most latter two exposure section in the process, and when performing step S1-S4 second, selected two exposure sections are in exposure process
Second-to-last exposes section and 3rd exposure section reciprocal, it is follow-up in and so on ground toward one exposure section of Forward, until all exposing
Light section is processed, that is, completes the recovery of high-dynamics image.
In one embodiment, referring to Fig. 3, on the basis of previous embodiment, it is segmented exposure image high dynamic recovery side
Method further includes step S5, and by way of gamma mapping curves, the size of the high-dynamics image after the completion of recovery is compressed mapping
To in the range of the bit wide of output.High-dynamics image is compressed by way of curve, effect due to original linear compression mode,
Image high dynamic range compression can be achieved.
Exposure image high dynamic recovery system is segmented the present invention also provides a kind of, including：
Pixel brightness value acquisition module：Perform each pixel brightness value for section last time of exposure T1 for obtaining the first exposure section
Each pixel brightness value Vi of section last time of exposure T of the exposure sections of V1i and second, i=1~n, n are the quantity of pixel, described
First exposure section is prior to the second exposure section；
Slope value computing module：The slope value K for calculating the corresponding current light intensity of each pixel is performed, wherein, K=(Vi-
V1i)/(T-T1)；
Current pixel brightness value computing module：The total exposure time T according to each slope value K and two exposure sections is performed,
Calculate the current pixel brightness value Vxi=K*T of each pixel；
Recovery module：It performs and an overexposure comparison range is determined according to the average overexposure value of the first exposure section, to each pixel
Brightness value V1i is compared judgement：
If pixel brightness value V1i does not reach the minimum value of the overexposure comparison range, final pixel brightness value Voi=Vi；
If pixel brightness value V1i is more than the maximum value of the overexposure comparison range, final pixel brightness value Voi=Vxi；
If pixel brightness value V1i in the overexposure comparison range, carries out fuzzy Judgment its tendency situation, according to tendency feelings
Condition determines final pixel brightness value Voi=Vi or final pixel brightness value Voi=Vxi.
According to one embodiment of present invention, it further includes：
Curve mapping unit is performed by way of gamma mapping, by the big of the high-dynamics image after the completion of recovery
Small compression is mapped in the range of the bit wide of output.
The particular content of segmentation exposure image high dynamic recovery system about the embodiment of the present invention may refer to aforementioned reality
The description as described in segmentation exposure image high dynamic restoration methods part in example is applied, details are not described herein.
Although the present invention is disclosed as above with preferred embodiment, it is not for limiting claim, any this field
Technical staff without departing from the spirit and scope of the present invention, can make possible variation and modification, therefore the present invention
Protection domain should be subject to the range that the claims in the present invention are defined.
Claims (10)
1. a kind of segmentation exposure image high dynamic restoration methods, which is characterized in that include the following steps：
S1：The section end for obtaining the exposure sections of each pixel brightness value V1i and second of section last time of exposure T1 of the first exposure section exposes
Light time carves each pixel brightness value Vi of T, and i=1~n, n are the quantity of pixel, and the first exposure section is prior to the second exposure
Section；
S2：The slope value K of the corresponding current light intensity of each pixel is calculated, wherein, K=(Vi-V1i)/(T-T1)；
S3：According to each slope value K and the total exposure time T of two exposure sections, the current pixel brightness of each pixel is calculated
Value Vxi=K*T；
S4：One overexposure comparison range is determined according to the average overexposure value of the first exposure section, each pixel brightness value V1i is compared
Compared with judgement：
If pixel brightness value V1i does not reach the minimum value of the overexposure comparison range, final pixel brightness value Voi=Vi；
If pixel brightness value V1i is more than the maximum value of the overexposure comparison range, final pixel brightness value Voi=Vxi；
It is true according to tendency situation if pixel brightness value V1i in the overexposure comparison range, carries out fuzzy Judgment its tendency situation
Determine final pixel brightness value Voi=Vi or final pixel brightness value Voi=Vxi.
2. segmentation exposure image high dynamic restoration methods as described in claim 1, which is characterized in that
When entire exposure image process is divided into two sections, then in the step S1, this two exposure sections are chosen, the first exposure section
Section last time of exposure T1 is the time of exposure of waypoint, and section last time of exposure T of the second exposure section performs to complete the time of exposure
Restore to complete after step S2-S4；
When exposing number of fragments more than two sections, two exposure sections are chosen from back to front and perform step S1-S4, after recovery
Pixel brightness value moves forward one and exposes section and choose corresponding two exposures section and perform step S1-S4, and so on until all
Exposure section is restored to complete.
3. segmentation exposure image high dynamic restoration methods as claimed in claim 2 or claim 3, which is characterized in that step S5 is further included,
By way of gamma mapping curves, the size compression of the high-dynamics image after the completion of recovery is mapped to the bit wide model of output
In enclosing.
4. segmentation exposure image high dynamic restoration methods as described in claim 1, which is characterized in that in the step S4, institute
Overexposure comparison range is stated as Vf A~Vf+A, Vf is the average overexposure value of the first exposure section, and A is luminance deviation value.
5. segmentation exposure image high dynamic restoration methods as claimed in claim 4, which is characterized in that the first exposure section
Average overexposure value is obtained for off-line test, and the value range of luminance deviation value A is 0~20.
6. segmentation exposure image high dynamic restoration methods as described in claim 1, which is characterized in that in the step S4, into
It is inclined to situation to row fuzzy Judgment, and final pixel brightness value Voi=Vi or final pixel brightness value Voi are determined according to tendency situation
=Vxi, including：
Centered on the pixels of pixel brightness value V1i in the overexposure comparison range, certain area is chosen；
Calculate the regional average value Vm's and each current pixel brightness value Vxi of each pixel brightness value Vi in the region respectively
Mean value Vxm；
The absolute value of the difference and Vs of each pixel brightness value Vi and its mean value Vxm and each current is calculated in the region respectively
The absolute value of the difference and Vxs of pixel brightness value Vxi and its mean value Vxm；
Judged, if Vxs ＜ Vs, Vo=Vxi, on the contrary Vo=Vi.
7. segmentation exposure image high dynamic restoration methods as claimed in claim 6, which is characterized in that selected regional extent
It is the region of the MxN pixel composition centered on the pixels in the overexposure comparison range of pixel brightness value V1i, it should
M, the equal values of N are 3~5.
8. segmentation exposure image high dynamic restoration methods as described in claim 1, which is characterized in that obtained in the step S1
The pixel brightness value taken obtains in the following manner：During exposure image, at the section end of the non-final exposure section for completing exposure
The time of exposure is stored after acquiring each pixel brightness value at the moment；And at the section end for the exposure section for being finally completed exposure
After the time of exposure acquires each pixel brightness value at the moment, the pixel brightness value of storage is obtained together, enters step in S2 and holds
Row.
9. a kind of segmentation exposure image high dynamic recovery system, which is characterized in that including：
Pixel brightness value acquisition module：Perform each pixel brightness value V1i for section last time of exposure T1 for obtaining the first exposure section
And second exposure section section last time of exposure T each pixel brightness value Vi, i=1~n, n are the quantity of pixel, described the
One exposure section is prior to the second exposure section；
Slope value computing module：The slope value K for calculating the corresponding current light intensity of each pixel is performed, wherein, K=(Vi-
V1i)/(T-T1)；
Current pixel brightness value computing module：The total exposure time T according to each slope value K and two exposure sections is performed, is calculated
The current pixel brightness value Vxi=K*T of each pixel；
Recovery module：It performs and an overexposure comparison range is determined according to the average overexposure value of the first exposure section, to each pixel intensity
Value V1i is compared judgement：
If pixel brightness value V1i does not reach the minimum value of the overexposure comparison range, final pixel brightness value Voi=Vi；
If pixel brightness value V1i is more than the maximum value of the overexposure comparison range, final pixel brightness value Voi=Vxi；
It is true according to tendency situation if pixel brightness value V1i in the overexposure comparison range, carries out fuzzy Judgment its tendency situation
Determine final pixel brightness value Voi=Vi or final pixel brightness value Voi=Vxi.
10. segmentation exposure image high dynamic recovery system as claimed in claim 9, which is characterized in that further include：
Curve mapping unit is performed by way of gamma mapping, by the size pressure of the high-dynamics image after the completion of recovery
Contracting is mapped in the range of the bit wide of output.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810042446.9A CN108234896B (en) | 2018-01-16 | 2018-01-16 | High dynamic recovery method and system for segmented exposure imaging |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810042446.9A CN108234896B (en) | 2018-01-16 | 2018-01-16 | High dynamic recovery method and system for segmented exposure imaging |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108234896A true CN108234896A (en) | 2018-06-29 |
| CN108234896B CN108234896B (en) | 2020-12-01 |
Family
ID=62641223
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810042446.9A Active CN108234896B (en) | 2018-01-16 | 2018-01-16 | High dynamic recovery method and system for segmented exposure imaging |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108234896B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110620878A (en) * | 2019-09-27 | 2019-12-27 | 思特威(上海)电子科技有限公司 | On-chip area exposure imaging method |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1671187A (en) * | 2004-03-15 | 2005-09-21 | 德鑫科技股份有限公司 | Method of exposure correction for digital image |
| US20070286592A1 (en) * | 2006-06-09 | 2007-12-13 | Asia Optical Co., Inc. | Method and system for automatic exposure compensation |
| EP2725783A1 (en) * | 2009-12-10 | 2014-04-30 | Samsung Electronics Co., Ltd | Multi-step exposure method using electronic shutter and photography apparatus using the same |
| CN104075994A (en) * | 2013-03-27 | 2014-10-01 | 上海铭源数康生物芯片有限公司 | Method for expansion of dynamic range of biochip detector and concentration back calculation based on fractional exposure |
| US20140362173A1 (en) * | 2013-06-06 | 2014-12-11 | Apple Inc. | Exposure Mapping and Dynamic Thresholding for Blending of Multiple Images Using Floating Exposure |
| CN104869332A (en) * | 2015-05-19 | 2015-08-26 | 北京空间机电研究所 | Method for adaptive multi-slope integration adjusting |
| CN106303274A (en) * | 2016-08-01 | 2017-01-04 | 凌云光技术集团有限责任公司 | A kind of high dynamic-range image synthesis method and device |
| US20170118456A1 (en) * | 2015-10-27 | 2017-04-27 | Research & Business Foundation Sungkyunkwan University | Method and system for determining optimal exposure time and number of exposures in structured light-based 3d camera |
-
2018
- 2018-01-16 CN CN201810042446.9A patent/CN108234896B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1671187A (en) * | 2004-03-15 | 2005-09-21 | 德鑫科技股份有限公司 | Method of exposure correction for digital image |
| US20070286592A1 (en) * | 2006-06-09 | 2007-12-13 | Asia Optical Co., Inc. | Method and system for automatic exposure compensation |
| EP2725783A1 (en) * | 2009-12-10 | 2014-04-30 | Samsung Electronics Co., Ltd | Multi-step exposure method using electronic shutter and photography apparatus using the same |
| CN104075994A (en) * | 2013-03-27 | 2014-10-01 | 上海铭源数康生物芯片有限公司 | Method for expansion of dynamic range of biochip detector and concentration back calculation based on fractional exposure |
| US20140362173A1 (en) * | 2013-06-06 | 2014-12-11 | Apple Inc. | Exposure Mapping and Dynamic Thresholding for Blending of Multiple Images Using Floating Exposure |
| CN104869332A (en) * | 2015-05-19 | 2015-08-26 | 北京空间机电研究所 | Method for adaptive multi-slope integration adjusting |
| US20170118456A1 (en) * | 2015-10-27 | 2017-04-27 | Research & Business Foundation Sungkyunkwan University | Method and system for determining optimal exposure time and number of exposures in structured light-based 3d camera |
| CN106303274A (en) * | 2016-08-01 | 2017-01-04 | 凌云光技术集团有限责任公司 | A kind of high dynamic-range image synthesis method and device |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110620878A (en) * | 2019-09-27 | 2019-12-27 | 思特威(上海)电子科技有限公司 | On-chip area exposure imaging method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108234896B (en) | 2020-12-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109785240B (en) | Low-illumination image enhancement method and device and image processing equipment | |
| CN105100632B (en) | The method of adjustment and device of imaging device automatic exposure, imaging device | |
| CN107590791B (en) | Image enhancement method and image processing apparatus | |
| CN108305232B (en) | A kind of single frames high dynamic range images generation method | |
| CN104604214A (en) | Method and apparatus for generating photograph image | |
| CN111294575A (en) | Image processing method, image processing device, electronic equipment and storage medium | |
| CN110111341B (en) | Image foreground obtaining method, device and equipment | |
| JP7010779B2 (en) | Image correction device and image correction method | |
| CN108234896A (en) | It is segmented exposure image high dynamic restoration methods and system | |
| CN114155173A (en) | Image defogging method and device and nonvolatile storage medium | |
| CN107369157A (en) | A kind of adaptive threshold Otsu image segmentation method and device | |
| CN110557572A (en) | image processing method and device and convolutional neural network system | |
| WO2021190745A1 (en) | Determination of illumination sections | |
| GB2588616A (en) | Image processing method and apparatus | |
| CN114565537B (en) | Infrared imaging device based on local information entropy | |
| CN113658068A (en) | Deep learning-based denoising enhancement system and method for CMOS camera | |
| TWI590192B (en) | Adaptive high dynamic range image fusion algorithm | |
| CN115082347A (en) | Image optimization method and device, electronic equipment and computer-readable storage medium | |
| GB2588674A (en) | Image processing | |
| KR102359138B1 (en) | Apparatus and method for customizable control of image brightness and contrast | |
| CN116912149B (en) | Image enhancement method and device and electronic equipment | |
| KR102584573B1 (en) | Integrated image processing apparatus and method for improving image quality using complex sensor information | |
| CN113225486B (en) | Processing method, device, equipment and medium for shot picture | |
| CN111091522B (en) | Terminal and multi-exposure image fusion method thereof | |
| JP5849590B2 (en) | Image processing method and image processing apparatus |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20200407 Address after: No. 338, Jinshun Road, Jinxi Town, Kunshan City, Suzhou City, Jiangsu Province Applicant after: KUNSHAN YEXIN ELECTRONIC TECHNOLOGY Co.,Ltd. Address before: Cayman Islands Applicant before: SmartSens Technology (Cayman) Co.,Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP03 | Change of name, title or address | ||
| CP03 | Change of name, title or address |
Address after: 215300 No. 188, Jinshun Road, Jinxi Town, Kunshan City, Suzhou City, Jiangsu Province Patentee after: Kunshan sitewei integrated circuit Co.,Ltd. Address before: No. 338, Jinshun Road, Jinxi Town, Kunshan City, Suzhou City, Jiangsu Province Patentee before: KUNSHAN YEXIN ELECTRONIC TECHNOLOGY Co.,Ltd. |