CN107045715B - A kind of method that single width low dynamic range echograms generate high dynamic range images - Google Patents
A kind of method that single width low dynamic range echograms generate high dynamic range images Download PDFInfo
- Publication number
- CN107045715B CN107045715B CN201710095753.9A CN201710095753A CN107045715B CN 107045715 B CN107045715 B CN 107045715B CN 201710095753 A CN201710095753 A CN 201710095753A CN 107045715 B CN107045715 B CN 107045715B
- Authority
- CN
- China
- Prior art keywords
- image
- dynamic range
- luminance component
- negative tone
- levels
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000012937 correction Methods 0.000 claims abstract description 21
- 238000013507 mapping Methods 0.000 claims abstract description 14
- 238000001914 filtration Methods 0.000 claims abstract description 10
- 230000004927 fusion Effects 0.000 claims abstract description 9
- 230000000007 visual effect Effects 0.000 claims abstract description 4
- 238000012545 processing Methods 0.000 claims description 8
- 230000002146 bilateral effect Effects 0.000 claims description 4
- 238000013459 approach Methods 0.000 claims 1
- 238000007493 shaping process Methods 0.000 claims 1
- 230000000694 effects Effects 0.000 abstract description 7
- 239000000284 extract Substances 0.000 abstract description 3
- 238000003384 imaging method Methods 0.000 description 7
- 238000006243 chemical reaction Methods 0.000 description 2
- 230000007812 deficiency Effects 0.000 description 2
- 230000001419 dependent effect Effects 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 238000000926 separation method Methods 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 230000034303 cell budding Effects 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 238000007499 fusion processing Methods 0.000 description 1
- 230000000574 ganglionic effect Effects 0.000 description 1
- 230000002401 inhibitory effect Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/50—Image enhancement or restoration by the use of more than one image, e.g. averaging, subtraction
-
- G06T5/70—
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20024—Filtering details
- G06T2207/20028—Bilateral filtering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20212—Image combination
- G06T2207/20221—Image fusion; Image merging
Abstract
The present invention proposes a kind of method that single width low dynamic range echograms generate high dynamic range images.This method is based on human-eye visual characteristic, the luminance component and chromatic component of low dynamic range echograms are isolated first, to side filtering of going bail for after luminance component progress gamma correction, extract the Primary layer of luminance component, traversal operation is carried out to Primary layer and luminance component again, obtains the levels of detail of luminance component；Then, negative tone mapping function is constructed, negative tone map operation is carried out to the luminance picture after levels of detail and gamma correction respectively, respective negative tone is obtained and reflects image；Later, luminance component is merged with levels of detail after negative tone being mapped, and obtains new luminance component；Finally, fusion chromatic component and new luminance component, and fused image degree of comparing is stretched and denoised, obtain final high dynamic range images.The present invention can obtain high dynamic range images by single width low dynamic range echograms, and treatment effect is good, strong operability, have wide applicability.
Description
Technical field
The present invention relates to image processing techniques, it relates in particular to a kind of details according to single width low dynamic range echograms
The single image high-dynamics image generation method that information carries out Multi-layer technology and merges again.
Technical background
In the past twenty years, high dynamic range (the high dynamic introduced by field of Computer Graphics
Range, HDR) Image Acquisition in the field and other field started revolutionary upsurge, such as photography, virtual reality,
Vision imaging, video-game etc..HDR imaging can be with the actual physics value of Direct Acquisition and utilization brightness.Image at
As during, very dark and very bright region may be recorded simultaneously in same frame image or the same video, be utilized
The actual physics value of brightness indicates that image can be to avoid the appearance in under-exposure and overexposure region in image.Traditional image is adopted
Set method does not use the actual physics value of brightness, and by technical restriction, can only handle the figure that every 8 bit of channel of every pixel indicates
Picture.Such image is referred to as low-dynamic range (low dynamic range, LDR) image.The change of brightness value recording method
Change, similar to the introducing of photochromy, causes to change in each stage of image processing pipeline.But directly
It obtains HDR image and needs specific capture device, and still image can only be obtained, the preparation method of dynamic HDR image is still located
Budding stage in the early stage.This just needs to study from LDR image the method for obtaining HDR image.These methods to show in HDR
Already existing a large amount of LDR images are re-used in equipment to be possibly realized.Moreover, the certain methods based on LDR to HDR extension are
Started to apply HDR image compression and in terms of.
Currently, the method for obtaining HDR image mainly has four classes.
The first kind carries out artificial treatment to image using image processing tools such as PhotoShop, and this method is due to people's
Directly participate in, can be according to different concrete conditions, actual to be handled, treatment effect is best, but there are unstability and when
Between cost it is high the disadvantages of.
Second class selects the imaging sensor with high dynamic range, and imaging effect is stablized, high-efficient, but captures image
Dynamic range it is still very limited, be generally referred to as wide dynamic (wide dynamic range, WDR) in this way.
This method is started with from hardware, using special dsp chip, in imaging by the way of being imaged line by line, for different light sources
It is exposed using different shutter speeds, is then handled and reconfigured by DSP, shooting the picture come so is directly exactly HDR
Image.Although this method is really more preferable than common capture apparatus shooting effect on imaging effect, and can shoot dynamic HDR figure
Picture, but it there are still deficiencies.Because within hardware, dynamic range and sensitivity are two conflicting factors, dynamic model
It is often relatively low to enclose big picture pick-up device its sensitivity, vice versa.That is wide dynamic camera equipment is in light condition
The image/video come is shot in the case where relatively good can usually show higher quality, but in the case where low-light (level),
Its image quality is not so good.
Third class synthesizes a width HDR image using the multiple image of multiple exposure, and this method is started with from software, applies at present
Most wide, the HDR picture pick-up device of many companies is also by the front end of the algorithm integration to picture pick-up device, and this method carries out HDR figure
As the strategy of imaging is broadly divided into two classes: one is different exposure images is chosen, by Function Fitting at HDR image, most
It is compressed into the LDR image for holding up to image information afterwards；Another kind is directly to merge to different exposure images, is used in combination
The ghost problem occurred in algorithm process fusion process.But this method needs to synthesize in several pictures, and this requires every
Image scene on width image cannot change too greatly, so can only shoot static HDR image mostly.
4th class is then to carry out HDR image based on single image to convert then being to generate width HDR figure using single width LDR image
Picture.This method mainly by the way of negative tone mapping operator, directly converts the LDR image of single width, can not only be real
The shooting of existing static state HDR image, moreover it is possible to carry out the recording of HDR video.It at the same time, in this way can also will be existing
A large amount of LDR images or video resource generate HDR resource, can be good at solving the problems, such as that HDR image or video resource are deficient.
Summary of the invention
It is an object of the invention to solve the problems, such as that low dynamic range echograms generate high dynamic range images, it is low to provide single width
The method that dynamic image directly generates high dynamic range images can get high dynamic range images by the method.
To achieve the goals above, the present invention provides a kind of single width low dynamic range echograms generation based on levels of detail separation
The method of high dynamic range images, wherein including mainly four parts, first part is pre-processed to LDR image；Second
Part is to processing image layered after pretreatment；Part III is that corresponding negative tone mapping processing is carried out to each tomographic image；4th
Part is to merge to obtain HDR image to separate picture.
First part includes two steps:
Step 1, the LDR image of input is converted into hsv color space from RGB color, isolatedH(coloration),S
(saturation degree) andV(brightness) component；
Step 2, gamma correction is carried out to the luminance component image isolated；
Second part includes two steps:
Step 3, operation is filtered to gamma correction image obtained in step 2 and obtains image Primary layer；
Step 4, by carrying out traversal arithmetic operation to gamma correction image and Primary layer, levels of detail is obtained；
Part III includes a step:
Step 5, negative tone mapping function is constructed, the school gamma of the levels of detail and step 2 acquisition that obtain respectively to step 4
Positive image carries out negative tone map operation, the image after obtaining respective negative tone mapping；
Part IV includes four steps:
Step 6, two width negative tones obtained in fusion steps 5 map image, obtain new luminance component image；
Step 7, saturation degree step 1 separatedS, chromatic componentHIt is merged with the luminance component that step 6 newly obtains
To the HDR image in hsv color space；
Step 8, the HDR image under hsv color space that step 7 obtains is transformed into RGB color；
Step 9, the image obtained in step 8 is subjected to denoising, eliminates noise, obtains final HDR image.
The invention proposes a kind of processing sides that single width low dynamic range echograms are converted into corresponding high dynamic range images
Method.This method is based on human vision system model, extracts the luminance component and coloration point of low dynamic range echograms respectively first
Amount extracts the Primary layer of luminance component, then to Primary layer to side filtering operation of going bail for after luminance component progress gamma correction
Traversal operation is carried out with luminance component, obtains the levels of detail of luminance component；Then, negative tone mapping function is constructed, respectively to thin
Luminance picture after ganglionic layer and gamma correction carries out negative tone map operation, obtains respective negative tone and reflects image；Later, will
Luminance component is merged with compressed levels of detail after negative tone mapping, obtains new luminance component.Finally, fusion coloration point
Amount and new luminance component, and fused image is adjusted, the contrast of image dark areas is further stretched, and pass through
Denoising operation plays a degree of inhibiting effect to the noise that levels of detail introduces.The present invention can pass through single width low-dynamic range figure
As obtaining high dynamic range images, treatment effect is preferable, and operational efficiency is high, has preferable robustness.
Detailed description of the invention
Fig. 1 is overall flow figure of the invention；
Fig. 2 is the flow chart that levels of detail of the invention separates；
Fig. 3 is the flow chart that negative tone of the invention maps；
Fig. 4 is the low dynamic range echograms of acquired original；
Fig. 5 is to utilize the high dynamic range tone mapping image after present invention processing Fig. 4.
Specific embodiment
In order to better understand the present invention, With reference to embodiment to the list of the invention based on levels of detail layering
Width low dynamic range echograms generate high dynamic range images method and are described in more detail.In description below, when
Perhaps, the detailed description of the preceding existing prior art can desalinate subject of the present invention content, these descriptions will be ignored herein.
Fig. 1 is a kind of specific embodiment flow chart of single width high dynamic range images generation method of the present invention, in this reality
It applies in scheme, follows the steps below:
Step 1, low dynamic range echograms 101 are obtained, such as Fig. 4；
Step 2, color notation conversion space 102 is carried out to low dynamic range echograms；
Used conversion formula is as follows:
Wherein,R、G、BThe pixel value of three components respectively in rgb space,H、S、VFor three components in HSV space
Value, max expression take the maximum value of pixel value in bracket, and min indicates to take the minimum value of pixel value in bracket.Because in HSV space
InHComponent is indicated with angle, therefore is worked asHWhen < 0, need byHComponent adds 360.
Step 3, being separated into the low dynamic range echograms of HSV spaceH103 He of componentS、VTwo components 104.
Step 4, gamma correction 105 is carried out to the luminance component image isolated；
Used gamma correction formula are as follows:
Wherein,I(x,y) be input picture pixel value,For the parameter of gamma correction, 1.5 ~ 2 are generally taken.
Step 5, to gamma correction image obtained in step 4, separation details layer operation is carried out, image detail layer is obtained,
Its specific steps is as shown in Figure 2:
(1) operation is filtered to gamma correction image 201 and obtains image Primary layer 202；
Here filtering operation selects nonlinear filtering such as bilateral filtering to handle original image.In two-sided filter
In, the value of output pixel is combined dependent on the weighted value of field pixel value, and formula is as follows:
It wherein, is imagefLocation point (k,l) pixel value,For the pixel value after bilateral filtering, weighting coefficientw
(i,j,k,l) depend on domain coreWith codomain coreProduct, wherein domain kernel representation are as follows:
Codomain kernel representation are as follows:
After the two is multiplied, the bilateral filtering weighting function dependent on data will be generated, as follows:
(2) traversal arithmetic operation is carried out by gamma correction image 201 and Primary layer 202, obtains levels of detail 203, formula
It is as follows:
Wherein,I b (x,y)Indicate the pixel value of basic tomographic image,I d (x,y)Indicate the pixel value of obtained levels of detail.
Step 7, new luminance component 107 is obtained by gamma correction image 105 and levels of detail 106, specific steps are such as
Shown in Fig. 3；
(1) negative tone map operation is carried out to gamma correction image 301 and levels of detail 302, respectively obtains negative tone and reflects
Rear image 303 and 304 is penetrated, formula is as follows:
Wherein,I in (x,y)It is the pixel value of image to be processed,I max Indicate that the maximum value of pixel in LDR image is mapped to
The size of the value of pixel in HDR image, that is, the maximum output brightness of image after extending；I white Determine that the extension of spread function is bent
Wire shaped, related to the contrast of mapped image, the present invention recommends to useI white =I max 。
(2) two width negative tones obtained in (1) are merged and maps image, obtain new luminance component image 305, formula is such as
Under:
Wherein,I 1 (x,y)、I 2 (x,y)It is that gamma correction image and levels of detail obtain after negative tone maps respectively
Image,、βIt is constant parameter, the present invention recommends to use。
Step 8, by coloration obtained in luminance component image 107 and step 2 new obtained in step 7, saturation degree point
Spirogram obtains the HDR image 108 under HSV space as 104 fusions；
Step 9, the HDR image 109 converted the HDR image 108 under HSV space under rgb space；
Step 10, the HDR image 109 under the rgb space obtained to step 9 carries out Gauss and denoises operation, obtains final
HDR image 110 after denoising, display effect such as Fig. 5 after HDR image tone mapping, formula are as follows:
The present invention is a kind of based on levels of detail to proposing according to single width low dynamic range echograms feature and human visual system
The single width low dynamic range echograms of layering generate high dynamic range images method, and this method is thin according to single width low dynamic range echograms
The feature of information deficiency is saved, human-eye visual characteristic is based on, the Primary layer of original image is isolated using filtering operation, and utilize original image
As obtaining different levels of detail from the nonidentity operation method of Primary layer, the image information that original image is hidden is excavated；Then structure
Rebellion tone mapping function carries out negative tone map operation to each tomographic image obtained；Finally merge each component and each layer
Image obtains high dynamic range images.Inventive algorithm is simple, strong operability, has wide applicability.
Although the illustrative specific embodiment of the present invention is described above, but it should be clear that the present invention is unlimited
In the range of specific embodiment, for those skilled in the art, as long as various change is in appended right
It is required that these variations are it will be apparent that all utilize present inventive concept in the spirit and scope of the present invention for limiting and determining
Innovation and creation in the column of protection.
Claims (4)
1. a kind of method that single width low dynamic range echograms generate high dynamic range images, which is characterized in that merged levels of detail
Layered approach and human-eye visual characteristic, the layered shaping of image after pretreatment, pretreatment including LDR image, each tomographic image into
The corresponding negative tone mapping processing of row, separate picture fusion obtain four parts of HDR image, and first part includes two steps:
Step 1, the LDR image of input is converted into hsv color space from RGB color, isolates chromatic componentH, saturation
Spend componentSAnd luminance componentV；
Step 2, gamma correction is carried out to the luminance component image isolated and obtains gamma correction image；
Second part includes two steps:
Step 3, to gamma correction image obtained in step 2Bilateral filtering is carried out to operate to obtain image Primary layer；
Step 4, the gamma correction image by being obtained to step 2The Primary layer obtained with step 3It carries out
Arithmetic operation is traversed, levels of detail is obtained, wherein the traversal formula used are as follows:
Part III includes a step:
Step 5, negative tone mapping function is constructed, the levels of detail obtained respectively to step 4The gamma obtained with step 2
Correct imageNegative tone map operation is carried out, the image after obtaining respective negative tone mappingWith
；Used negative tone mapping function is as follows:
Wherein,I in (x,y) be image to be processed pixel value,I max Indicate that the maximum value of pixel in LDR image is mapped to HDR figure
The size of the value of pixel as in, that is, the maximum output brightness of image after extending；I white Determine the expansion curve shape of spread function
Shape is related to the contrast of mapped image；
Part IV includes four steps:
Step 6, two width negative tones obtained in fusion steps 5 map imageWith, obtain new luminance component
Image；Used fusion formula is as follows:
Wherein,I 1(x,y)、I 2(x,y) it is the image that gamma correction image and levels of detail obtain after negative tone maps respectively,、βIt is constant parameter;
Step 7, saturation degree component step 1 separatedS, chromatic componentHThe luminance component newly obtained with step 6Into
Row fusion obtains the HDR image in hsv color space；
Step 8, the HDR image under hsv color space that step 7 obtains is transformed into RGB color；
Step 9, the image obtained in step 8 is subjected to denoising, eliminates noise, obtains final HDR image.
2. the method that a kind of single width low dynamic range echograms according to claim 1 generate high dynamic range images, special
Sign is, the traversal arithmetic operation between the image of step 4 is separated into single image using the bilateral filtering operation of step 3 more
Layer, i.e. Primary layer and levels of detail, are handled.
3. the method that a kind of single width low dynamic range echograms according to claim 1 generate high dynamic range images, special
Sign is, in step 5I white Choosing method beI white =I max。
4. the method that a kind of single width low dynamic range echograms according to claim 1 generate high dynamic range images, special
Sign is that the parameter of fusion formula is selected as in step 6。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710095753.9A CN107045715B (en) | 2017-02-22 | 2017-02-22 | A kind of method that single width low dynamic range echograms generate high dynamic range images |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710095753.9A CN107045715B (en) | 2017-02-22 | 2017-02-22 | A kind of method that single width low dynamic range echograms generate high dynamic range images |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107045715A CN107045715A (en) | 2017-08-15 |
| CN107045715B true CN107045715B (en) | 2019-06-07 |
Family
ID=59545554
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710095753.9A Active CN107045715B (en) | 2017-02-22 | 2017-02-22 | A kind of method that single width low dynamic range echograms generate high dynamic range images |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107045715B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110852956A (en) * | 2019-07-22 | 2020-02-28 | 江苏宇特光电科技股份有限公司 | Method for enhancing high dynamic range image |
Families Citing this family (23)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107370963B (en) * | 2017-08-28 | 2023-08-08 | 北京地平线信息技术有限公司 | Image processing method, image processing device and electronic equipment |
| CN107657594A (en) * | 2017-09-22 | 2018-02-02 | 武汉大学 | The quick tone mapping method and system of a kind of high quality |
| CN109698910A (en) * | 2017-10-23 | 2019-04-30 | 北京京东尚科信息技术有限公司 | The generation method and device of high dynamic range photo, electronic equipment, storage medium |
| CN107895350B (en) * | 2017-10-27 | 2020-01-03 | 天津大学 | HDR image generation method based on self-adaptive double gamma transformation |
| CN108305232B (en) * | 2018-03-01 | 2019-07-12 | 电子科技大学 | A kind of single frames high dynamic range images generation method |
| CN108717690B (en) * | 2018-05-21 | 2022-03-04 | 电子科技大学 | Method for synthesizing high dynamic range picture |
| CN110930311B (en) * | 2018-09-19 | 2023-04-25 | 杭州萤石软件有限公司 | Method and device for improving signal-to-noise ratio of infrared image and visible light image fusion |
| CN109284719A (en) * | 2018-09-28 | 2019-01-29 | 成都臻识科技发展有限公司 | A kind of primary data processing method and system based on machine learning |
| CN109360180A (en) * | 2018-10-23 | 2019-02-19 | 凌云光技术集团有限责任公司 | A kind of method and device obtaining multiframe wide dynamic images |
| KR102569375B1 (en) | 2018-10-24 | 2023-08-22 | 삼성전자주식회사 | Electronic device and controlling method thereof |
| CN109448640A (en) * | 2018-10-29 | 2019-03-08 | 天津大学 | A kind of HDR image display methods based on LCD-LED double modulation high dynamic display |
| KR20200053125A (en) | 2018-11-08 | 2020-05-18 | 삼성전자주식회사 | Electronic device and control method thereof |
| CN111260876B (en) * | 2018-11-30 | 2022-02-25 | 北京欣奕华科技有限公司 | Image processing method and device |
| CN109785263B (en) * | 2019-01-14 | 2022-09-16 | 北京大学深圳研究生院 | Retinex-based inverse tone mapping image conversion method |
| WO2020206659A1 (en) * | 2019-04-11 | 2020-10-15 | Thunder Software Technology Co., Ltd. | Method and apparatus for combining low-dynamic range images to a single image |
| CN110365914B (en) * | 2019-07-24 | 2020-03-20 | 中国人民解放军国防科技大学 | Image dynamic range widening method and system |
| CN110378859B (en) * | 2019-07-29 | 2022-03-11 | 西南科技大学 | Novel high dynamic range image generation method |
| CN111899178B (en) | 2020-08-18 | 2021-04-16 | Oppo广东移动通信有限公司 | Image processing method, image processing system, electronic device, and readable storage medium |
| CN116324869A (en) * | 2020-08-28 | 2023-06-23 | 西安诺瓦星云科技股份有限公司 | Method and device for correcting brightness and chrominance |
| CN112887597A (en) * | 2021-01-25 | 2021-06-01 | Oppo广东移动通信有限公司 | Image processing method and device, computer readable medium and electronic device |
| CN112861988B (en) * | 2021-03-04 | 2022-03-11 | 西南科技大学 | Feature matching method based on attention-seeking neural network |
| CN114429426B (en) * | 2021-12-20 | 2022-08-16 | 哈尔滨理工大学 | Low-illumination image quality improvement method based on Retinex model |
| CN114359083B (en) * | 2021-12-24 | 2022-11-29 | 北京航空航天大学 | High-dynamic thermal infrared image self-adaptive preprocessing method for interference environment |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104463820A (en) * | 2014-10-29 | 2015-03-25 | 广东工业大学 | Reverse tone mapping algorithm based on frequency domain |
| EP2958076A1 (en) * | 2014-06-20 | 2015-12-23 | Thomson Licensing | Method and apparatus for dynamic range expansion of LDR video sequence |
| CN105850114A (en) * | 2013-12-27 | 2016-08-10 | 汤姆逊许可公司 | Method for inverse tone mapping of an image |
-
2017
- 2017-02-22 CN CN201710095753.9A patent/CN107045715B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105850114A (en) * | 2013-12-27 | 2016-08-10 | 汤姆逊许可公司 | Method for inverse tone mapping of an image |
| EP2958076A1 (en) * | 2014-06-20 | 2015-12-23 | Thomson Licensing | Method and apparatus for dynamic range expansion of LDR video sequence |
| CN104463820A (en) * | 2014-10-29 | 2015-03-25 | 广东工业大学 | Reverse tone mapping algorithm based on frequency domain |
Non-Patent Citations (4)
| Title |
|---|
| A Novel Approach for Detail-Enhanced Exposure Fusion Using Guided Filter;Harbinder Singh et al;《the Scientific World Journal》;20141231;第2014卷;第1-8页 |
| Stream Processor for Real-Time Inverse Tone Mapping of Full-HD Images;Gian Domenico Licciardo et al;《IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS》;20151130;第23卷(第11期);第2532-2539页 |
| 单幅图像的高动态范围图像生成方法;朱恩弘 等;《计算机辅助设计与图形学学报》;20161031;第28卷(第10期);第1713-1722页 |
| 高动态范围图像及反色调映射算子;霍永青 等;《系统工程与电子技术》;20120430;第34卷(第4期);第820-826页 |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110852956A (en) * | 2019-07-22 | 2020-02-28 | 江苏宇特光电科技股份有限公司 | Method for enhancing high dynamic range image |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107045715A (en) | 2017-08-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107045715B (en) | A kind of method that single width low dynamic range echograms generate high dynamic range images | |
| US9589335B2 (en) | Method for dynamic range editing | |
| Shen et al. | Exposure fusion using boosting Laplacian pyramid. | |
| TWI464706B (en) | Dark portion exposure compensation method for simulating high dynamic range with single image and image processing device using the same | |
| CN108492262B (en) | No-ghost high-dynamic-range imaging method based on gradient structure similarity | |
| Jacobs | High dynamic range imaging and its application in building research | |
| Vonikakis et al. | Multi-exposure image fusion based on illumination estimation | |
| US20120183210A1 (en) | Method and a Device for Merging a Plurality of Digital Pictures | |
| Klein et al. | Simulating low-cost cameras for augmented reality compositing | |
| Ward et al. | High dynamic range imaging & image-based lighting | |
| Yan et al. | Enhancing image visuality by multi-exposure fusion | |
| CN111105359A (en) | Tone mapping method for high dynamic range image | |
| Chaurasiya et al. | High dynamic range imaging | |
| Rouf et al. | Gradient domain color restoration of clipped highlights | |
| JP4359662B2 (en) | Color image exposure compensation method | |
| Lapray et al. | Smart camera design for realtime high dynamic range imaging | |
| Hu et al. | High dynamic range imaging with short-and long-exposures based on artificial remapping using multiscale exposure fusion | |
| CN110246086A (en) | The image processing method and its image processing system of color image enhancement | |
| Shen et al. | Recovering high dynamic range by Multi-Exposure Retinex | |
| JP5050141B2 (en) | Color image exposure evaluation method | |
| TW201216697A (en) | Image processing method | |
| Fan et al. | Underwater image enhancement algorithm combining color correction and multi-scale fusion | |
| Singh et al. | Detail Enhanced Multi-Exposer Image Fusion Based on Edge Perserving Filters | |
| Lakshmi et al. | Analysis of tone mapping operators on high dynamic range images | |
| Sujatha et al. | Analysis and Epigrammatic Study of Various Tone Mapping Operators for High Dynamic Range Images |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |