CN105930117A - Super-8-bit gradation measuring image universe display method - Google Patents
Super-8-bit gradation measuring image universe display method Download PDFInfo
- Publication number
- CN105930117A CN105930117A CN201610231506.2A CN201610231506A CN105930117A CN 105930117 A CN105930117 A CN 105930117A CN 201610231506 A CN201610231506 A CN 201610231506A CN 105930117 A CN105930117 A CN 105930117A
- Authority
- CN
- China
- Prior art keywords
- gray
- image
- grades
- scale
- pixel
- 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
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/14—Digital output to display device ; Cooperation and interconnection of the display device with other functional units
- G06F3/1407—General aspects irrespective of display type, e.g. determination of decimal point position, display with fixed or driving decimal point, suppression of non-significant zeros
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Human Computer Interaction (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Image Processing (AREA)
Abstract
The invention discloses a technology of a super-8-bit gradation measuring image universe display. A super-8-bit gradation measuring image is mapped on multiple same-sized 8-bit 256 gradation images for completely displaying all information of the image. By means of the method, feeble target details can be kept which is of great importance for extracting and analyzing objects of measured images.
Description
Technical field
The invention belongs to image measurement field, be specifically related to one and surpass 8 gray scales measurement image universe display packings.
Background technology
Being presently used for the imageing sensor typically above 8 measured, majority is 12 or 14, its gray scale produced
Measuring image to be made up of pixel grey scale matrix, the half-tone information of each pixel accounts for 12, up to 4096 grades gray scales or account for
14, up to 16384 grades gray scales, it is far longer than 8 256 grades of gray scales that windows operating system can show.Cause
This, current commonly used compression gray level method for distinguishing, by 4096 grades or 16384 grades of gray compressions to 256 grades, but, this must
So cause the loss of image information, reduce the display capabilities of weak target.So, the present invention looks for another way, and uses and does not compress figure
As grey level, but the method that 12 or 14 gray level image subsection compression are become some 8 gray level images, it is achieved measure
The universe of image information shows.
Summary of the invention
In view of this, the invention provides a kind of universe display packing surpassing 8 gray scales measurement images, it is possible to show 14
Gray scale measures the weak target in image.
Realize technical scheme as follows:
One surpasses 8 gray scales and measures image universe display packing, comprises the following steps:
Step one, foundation surpass 8 gray scales and measure the image histogram of images, and wherein, x coordinate is grey scale pixel value, y-coordinate
For having the number of pixels of this gray-scale value；
Step 2, intercepting surpass 8 gray scales and measure the available gray-scale interval of images；Starting point g that available gray-scale is interval1For: g1=
[glow+(ghigh-glow) × 4.5%], terminal g2For: g2=[ghigh-(ghigh-glow) × 3.5%].Wherein, glowFor surpassing 8 ashes
Degree measures the lowest gray value of all pixels, g in imagehighThe highest gray scale of all pixels in image is measured for surpassing 8 gray scales
Value, [...] is for rounding downwards symbol；
Step 3, from interval starting point g of available gray-scale1Starting, pixel-map corresponding in every 256 grades of gray scale intervals becomes one
The image of 256 grades of gray scales；When last gray scale interval is discontented with 256 grades, by the gray level equal proportion in this gray scale interval
In the range of being amplified to 256 grades；Wherein, the i-th row in n-th 256 grades of gray level image, the grey scale pixel value G of jth row(i,j)For:
Gn(i,j)=[(g(i,j)-256(n-1)-g1)×k],g(i,j)The gray scale of the i-th row jth row pixel in image is measured for surpassing 8 gray scales
Value,K is amplification coefficient, and when gray scale interval is 256, k=1, when last gray scale interval is discontented with
When 256 grades,If Gn(i,j)＞ 256 or Gn(i,j)＜ 0, then Gn(i,j)=0.
Beneficial effect: all information of the display image that the present invention can be complete, retains the details of weak target, for surveying
Objective extraction and the analysis of spirogram picture have greater significance.
Accompanying drawing explanation
Fig. 1 is in the present invention, 1 14 16384 grades of gray scale to be measured image to be mapped to 4 width with 8 256 grades of gray scales of size
The schematic diagram of image.
Detailed description of the invention
Develop simultaneously embodiment below in conjunction with the accompanying drawings, describes the present invention.
As it is shown in figure 1, the invention provides one to surpass 8 gray scales measurement image universe display packings, comprise the following steps:
Step one, initially set up and surpass 8 gray scales and measure the image histogram of images, this example uses one 14 16384
Level gray scale measures image.Wherein, x coordinate is grey scale pixel value, and y-coordinate is the number of pixels with this gray-scale value.14
It is g that 16384 grades of gray scales measure the lowest gray value of all pixels in imagelow=955, surpass 8 gray scales and measure all pictures in image
The highest gray value of element is ghigh=1971；I.e. glowAnd ghighFor the tonal range of entire image, in figure, curve represents have certain
The number of pixels of gray-scale value, for the image of relatively weak signal target, grey level shared by its background and pixel count large percentage, and micro-
Weak signal target proportion is less, therefore, directly carries out compression of grey levels, easily causes the loss of weak target information.
The available gray-scale that step 2,14 16384 grades of gray scales of intercepting measure images is interval.Starting point g that available gray-scale is interval1
For: g1=[glow+(ghigh-glow) × 4.5%], specifically it is calculated as: g1=[955+ (1971-955) × 4.5%]=1001；Eventually
Point g2For: g2=[ghigh-(ghigh-glow) × 3.5%], specifically it is calculated as: g2=[1971-(1971-955) × 3.5%]=
1935.Wherein, glowIt is that 14 16384 grades of gray scales measure the lowest gray value of all pixels, g in imagehighIt it is 14 16384
Level gray scale measures the highest gray value of all pixels in image, and [...] is for rounding downwards symbol.Since then, available gray-scale district is obtained
Between be 1001～1935.
Step 3, from the beginning of the starting point 1001 that available gray-scale is interval, every 256 grades of gray scale intervals are mapped as one 8 256 grades
Gray level image, the most respectively by 1001～1257,1257～1531,1531～1769,1769～1935 in gray scale interval corresponding
Pixel is respectively mapped to 48 256 grades of gray scales with in the image of size；In each image, the mapping gray-scale value of pixel is
Gn(i,j)=[(g(i,j)-256(n-1)-g1) × k], wherein, i, j are the ranks number of pixel in image, and n is the figure film size mapped
Number,K is amplification coefficient, and when gray scale interval is 256, k=1, when last gray scale interval is discontented with
When 256 grades,If Gn(i,j)＞ 256 or Gn(i,j)＜ 0, then Gn(i,j)=0.
As for piece image the 1st row, the pixel of the 1st row, the gray value of corresponding original image same position pixel is
g(1,1)=1034,K=1, Gn(1,1)=[(1034-256 × (1-1)-1001) × 1]=33.With
Sample, the 4th row, the grey scale pixel value G of the 1st rown(4,1)=[(1034-256 × (1-1)-1001) × 1]=33.Other picture in image
Element calculates successively, if Gn(i,j)＞ 256 or Gn(i,j)＜ 0, then Gn(i,j)=0.
For the second width image the 3rd row, the pixel of the 1st row, the gray value of corresponding original image same position pixel is g(3,1)
=1489,K=1, Gn(3,1)=[(1489-256 × (2-1)-1001) × 1]=232.Image
In other pixel calculate successively, if Gn(i,j)＞ 256 or Gn(i,j)＜ 0, then Gn(i,j)=0.
For the 3rd width image the 2nd row, the pixel of the 1st row, the gray value of corresponding original image same position pixel is g(2,1)
=1567,K=1, Gn(2,1)=[(1567-256 × (3-1)-1001) × 1]=54.Image
In other pixel calculate successively, if Gn(i,j)＞ 256 or Gn(i,j)＜ 0, then Gn(i,j)=0.
For the 4th width image, owing to its tonal range is 1769～1935, less than 256, therefore, when gray value maps,
Must equivalent step by step amplify, its amplification coefficient is:Concrete each pixel calculates
Mode is as follows:
For the 2nd row, the pixel of the 2nd row, the gray value of corresponding original image same position pixel is g(2,2)=1890,Gn(2,2)=[(1890-256 × (4-1)-1001) × 1.542]=187.
For the 2nd row, the pixel of the 3rd row, the gray value of corresponding original image same position pixel is g(2,3)=1853,Gn(2,3)=[(1853-256 × (4-1)-1001) × 1.542]=130.
For the 2nd row, the pixel of the 4th row, the gray value of corresponding original image same position pixel is g(2,4)=1844,Gn(2,4)=[(1844-256 × (4-1)-1001) × 1.542]=116.
In image, other pixel calculates successively, if Gn(i,j)＞ 256 or Gn(i,j)＜ 0, then Gn(i,j)=0.
Since then, 48 256 grades of gray level images will be become by 1 14 16384 grades of gray level image subsection compression, it is achieved measure
The universe of image information shows.
In sum, these are only presently preferred embodiments of the present invention, be not intended to limit protection scope of the present invention.
All within the spirit and principles in the present invention, any modification, equivalent substitution and improvement etc. made, should be included in the present invention's
Within protection domain.
Claims (1)
1. one kind surpasses 8 gray scales measurement image universe display packings, it is characterised in that comprise the following steps:
Step one, foundation surpass 8 gray scales and measure the image histogram of images, and wherein, x coordinate is grey scale pixel value, and y-coordinate is tool
There is the number of pixels of certain grade of gray value；
Step 2, intercepting surpass 8 gray scales and measure the available gray-scale interval of images；Starting point g that available gray-scale is interval1For: g1=[glow
+(ghigh-glow) × 4.5%], terminal g2For: g2=[ghigh-(ghigh-glow) × 3.5%].Wherein, glowSurvey for surpassing 8 gray scales
The lowest gray value of all pixels, g in spirogram picturehighThe highest gray value of all pixels in image is measured for surpassing 8 gray scales,
[...] is for rounding downwards symbol；
Step 3, from interval starting point g of available gray-scale1Starting, pixel-map corresponding in every 256 grades of gray scale intervals becomes a width same
8 256 grades of gray level images of size；When last gray scale interval is discontented with 256 grades, by the gray level etc. in this gray scale interval
In the range of scaling to 256 grades.I-th row in n-th 8 256 grades of gray level image, the grey scale pixel value G of jth row(i,j)For:
Gn(i,j)=[(g(i,j)-256(n-1)-g1) × k], wherein, i, j are the ranks number of pixel in image, g(i,j)Survey for surpassing 8 gray scales
The gray value of the i-th row jth row pixel in spirogram picture；N is the figure film size number mapped,K is amplification coefficient,
When gray scale interval is 256 grades, k=1, when last gray scale interval is discontented with 256 grades,If
Gn(i,j)＞ 256 or Gn(i,j)＜ 0, then Gn(i,j)=0.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610231506.2A CN105930117B (en) | 2016-04-14 | 2016-04-14 | One kind surpassing 8 gray scales and measures image universe display methods |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610231506.2A CN105930117B (en) | 2016-04-14 | 2016-04-14 | One kind surpassing 8 gray scales and measures image universe display methods |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105930117A true CN105930117A (en) | 2016-09-07 |
| CN105930117B CN105930117B (en) | 2018-08-24 |
Family
ID=56839106
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610231506.2A Active CN105930117B (en) | 2016-04-14 | 2016-04-14 | One kind surpassing 8 gray scales and measures image universe display methods |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105930117B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5663772A (en) * | 1994-03-29 | 1997-09-02 | Matsushita Electric Industrial Co., Ltd. | Gray-level image processing with weighting factors to reduce flicker |
| US20070058201A1 (en) * | 2005-09-14 | 2007-03-15 | Takahiro Ike | Image processing method, program and image processing apparatus |
| CN101527829A (en) * | 2008-03-07 | 2009-09-09 | 华为技术有限公司 | Method and device for processing video data |
| CN104657960A (en) * | 2013-11-25 | 2015-05-27 | 中国科学院沈阳自动化研究所 | Gray level image contrast drawing method and device |
| CN105488774A (en) * | 2015-12-05 | 2016-04-13 | 中国航空工业集团公司洛阳电光设备研究所 | Gray transformation method and device for image display |
-
2016
- 2016-04-14 CN CN201610231506.2A patent/CN105930117B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5663772A (en) * | 1994-03-29 | 1997-09-02 | Matsushita Electric Industrial Co., Ltd. | Gray-level image processing with weighting factors to reduce flicker |
| US20070058201A1 (en) * | 2005-09-14 | 2007-03-15 | Takahiro Ike | Image processing method, program and image processing apparatus |
| CN101527829A (en) * | 2008-03-07 | 2009-09-09 | 华为技术有限公司 | Method and device for processing video data |
| CN104657960A (en) * | 2013-11-25 | 2015-05-27 | 中国科学院沈阳自动化研究所 | Gray level image contrast drawing method and device |
| CN105488774A (en) * | 2015-12-05 | 2016-04-13 | 中国航空工业集团公司洛阳电光设备研究所 | Gray transformation method and device for image display |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105930117B (en) | 2018-08-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103994724B (en) | Structure two-dimension displacement and strain monitoring method based on digital image processing techniques | |
| CN103530896A (en) | Image compression and detail enhancement method for infrared image | |
| CN102789578B (en) | Infrared remote sensing image change detection method based on multi-source target characteristic support | |
| CN111598869B (en) | Method, equipment and storage medium for detecting Mura of display screen | |
| TW201250608A (en) | Image comparison system and method | |
| CN103377468A (en) | Image processing device and image processing method | |
| CN110197185B (en) | Method and system for monitoring space under bridge based on scale invariant feature transform algorithm | |
| CN102693067A (en) | System and method for adjusting font size | |
| PL1802960T3 (en) | Sight distance measuring device | |
| CN101193202A (en) | Method for display highly dynamic image on the traditional output device | |
| Wei et al. | Detecting damaged buildings using a texture feature contribution index from post-earthquake remote sensing images | |
| Wang et al. | Remote sensing image enhancement based on orthogonal wavelet transformation analysis and pseudo-color processing | |
| CN109376599A (en) | A kind of remote sensing image processing method and system extracted towards wetland information | |
| US20220254169A1 (en) | Road surface inspection apparatus, road surface inspection method, and program | |
| CN104851102B (en) | A kind of infrared small target detection method based on human visual system | |
| CN102254306B (en) | Real-time image defogging method based on image simplified hierachical model | |
| CN1945353A (en) | Method for processing meteorological satellite remote sensing cloud chart | |
| CN117854402A (en) | Abnormal display detection method and device of display screen and terminal equipment | |
| Luciani et al. | The impact of image and class structure upon sub-pixel mapping accuracy using the pixel-swapping algorithm | |
| CN1323545C (en) | Method for determining automatic detection threshold of bad pixel of medical image | |
| CN105930117B (en) | One kind surpassing 8 gray scales and measures image universe display methods | |
| Shinozaki et al. | Detection of deterioration of furnace walls using large-scale point-clouds | |
| CN105488774A (en) | Gray transformation method and device for image display | |
| CN103096035B (en) | Monitor with video optimization function | |
| CN116067474A (en) | Electronic platform scale intelligent verification method based on deep learning detection and identification |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |