The monitors and printers calibration arises from the professional editorial/photographic world need to work with the images displayed by a monitor and obtain a print with the same visual perception. Two operations are required to achieve this:
To calibrate the monitor response and create a numerical map of correspondence between the RGB components and what is displayed by the monitor (profiling), this data is stored in a file named ICC Profile. The monitor calibration is performed by means of spectrometers and colorimeters that manage the color by rules and standards defined by the ICC (International Color Consortium).
To calibrate the printer response and create a numerical map of correspondence between the RGB components and what is printed (profiling), this data is stored in a file named ICC Profile. The printer calibration is performed using spectrometers.
For what concerns the monitor calibration and profiling can also be performed by the manufacturer because the monitor screen is preset and in this case it could be possible to buy a monitor already calibrated and profiled, for the printer instead calibration and profiling depend not just on the ink but also on the paper used for printing, so the ICC profiles provided by the manufacturer may not be adequate to the printing needs and in this case it would be necessary to manually calibrate and profile. We remember that printers have a much narrower colour range (gamut) than monitors so when calibrating the monitor you need to impose constraints so as to improve the matching between the image on the screen and the printed image. For this reason the optimal constraints for printing are less suitable for just displaying the image on the screen.
You can calibrate the monitor just for images direct vision with our eyes, in this case the calibration parameters should be adjusted accordingly. The image accuracy is always related to the system to which the calibration is directed to.
Personally, to adjust the monitor screen I have always displayed bright and dark images and then adjusted the brightness and contrast to obtain an adjustment that allows to display all image types in an acceptable way. This is an empirical procedure that is more based on sensation than on objective assessment. For some videogames small changes in brightness and contrast could be made without knowing if the problem is with the monitor or the videogame. As I don’t have a photometer/colorimeter available I raised myself two questions:
- Is it possible to build a vision-based calibration system that can obtain objectively valid results?
- How do I build this system?
To answer these questions I inspired myself to ancient Egypt: about 3000 years ago by a palm leaf, a plumb bob and a square the Egyptians built an instrument known as the “Merkhet” used to measure the fields, perfectly align the pyramids blocks, perform the first astronomical observations following the stars, build portable watches to know the time both during the day and at night, all with a simple geometry and arithmetic. Now we don’t have the mission to illuminate the human civilization path, but simply to illuminate properly the screen of our monitor. The idea is to substitute the elements that constitute the Merkhet with others that can help us achieve our goal:
BOT Merkhet RGB-ENG
Fig.1 – Merkhet-RGB Project
Fig.2 – Egyptian Merkhet (Image owned by London Science Science Museum Group)
By using the controls of the video card that displays appropriate sample images and the support of a suitable calibration procedure I believe that our Merkhet-RGB can work. As said Albert Einstein: “It’s better to be an optimist and be wrong, rather than be a pessimist and be right”. The tutorial focus is to design the sample images and the calibration procedure.
THE REAL MONITOR
In the previous tutorial at §1. we defined some basic concepts about the digital image processing theory, now we add those necessary to calibrate a real monitor. In an ideal monitor at each gray tone of the image to be displayed corresponds to a unique gray tone in the image displayed for all 256 tones, and the grayscale is perfectly linear as RGB components linearity consequence.
The three RGB components have in common both black and white, but the black is unique whereas the white isn’t unique and needs to be characterized. To understand this asymmetry it’s enough to think about how we perceive colors: if we look at an object lit by the sun at noon we see the object in black if the sunlight that strikes it isn’t reflected towards our eyes, on the opposite if it reflects all the light we see the object in white. If we look at a white object at sunset we always see it as white but it tends towards the orange color, while if we look at it on a clear sky day we see it as white slightly bluish. An object that doesn’t reflect the sunlight we see it black in any situation. The LED monitor black intensity is depending on the technology used to produce the screen and is in no way adjustable, unlike the cathode ray tube (CRT) monitors for which adjustment was required. It’s necessary to adjust the white chromaticity known as the White Point.
- How to specify the White Point ?
The visible light colors are electromagnetic waves with wavelengths ranging from 700 nanometers for red to 400 nanometers for violet. The color-wavelength relation isn’ t biunivocal, to every wavelength we can associate a color but to every color we perceive doesn’t correspond a single wavelength. This is because colors are physically a mixture of electromagnetic waves of different wavelengths or the sum of other colors. Just the laser light is quasi monochromatic.
To indicate the White Point we use the model that in physics is named “black body”, which is an object that absorbs all the light without reflecting anything and he is in thermal equilibrium, i.e. emits all the absorbed energy. In this model the emitted energy has wavelengths that are depending on the temperature of the black body. The unit of measure used is the “kelvin” (absolute temperature), the zero of the kelvin scale (0(K)) is the lowest temperature achievable by an object in the universe and corresponds to -273.15°C (conversion rule T(K)=T(°C)+ 273.15 with T(K)>0).
By observing the black body at increasing temperatures we will see it according to the following temperature-color diagram also used to indicate the White Point:
BOT White Point – ENG
The white point choice is a psychology/aesthetics matter of what we consider natural. Our visual apparatus interprets light with a white hue the light with a around 5,500 K colour temperature corresponding to sunlight at the zenith. Below and above this temperature value the light is sensed as warm or cold respectively.
The white point temperature is a crucial element for the monitor calibration: the key topic lasted years of research is that the 5000K color temperature, the standard for printing, allows a complete chromatic adaptation of the observer for printing, but not for viewing on the monitor whose standard is 6500K. Instead, the 6500K colour temperature allows this adaptation also on the monitor, but doesn’t allow the printed images with the displayed ones comparison. Those who want to work with images displayed on a correctly calibrated system for printing should find a compromise converging to 5000K, while those who simply want to display images correctly on the screen can use the 6500K color temperature without problems.
Note: We used the kelvin as the measurement unit, actually the ISO 3664 standard which is the international color viewing standard for the graphic technology and photography industries uses the concept of “Daylight” temperature, prefixed by “D”, where the color temperature is depending on both the light source and the reflective characteristics of the lighted surface. This standard no longer refers to a 5000K/6500K colour temperature for example, but to a D50/D65 colour temperature. This is a specific topic for printing, for what interests us we will continue to use the color temperature in kelvin.
The white intensity is depending on the system physical characteristics that emits it.
- How to specify the white intensity ?
The light intensity represents the light (photon) concentration in a given direction emitted every second. This quantity is known as “luminance ” and is measured in candle/m2 (cd/m2). The higher is the luminance, the brighter is the white perceived by the eye. A well lit white paper sheet has a 100/120 cd/m2 luminance while the monitors have luminance up to +1000 cd/m2 and the highest values are for gaming monitors (up to 400 cd/m2) and those with HDR or for outdoor use. If the monitor calibration is aimed at printing then during the calibration phase it’s “mandatory” to choose a luminance between 100 and 120 cd/m2 and the reason is simple: the printed image is view by reflection of light instead the monitor image is view by light emission. The bright white and the higher contrast on the whole colour scale is certainly enjoyable but with a luminance higher than 120 cd/m2 the print feeling is too different from what is shown on the monitor. Every activity has the right monitor and calibration.
Now we have reached another crucial point for the real monitors: we saw that for an ideal monitor the RGB components are perfectly linear and the image to be displayed tones are in correspondence 1:1 with those of the image displayed. In the real world all technologies have manufacturing limitations and for monitors this is translated into the RGB components non-linearity for the displayed image.
- How do we correct this defect?
To better understand the facts we take a step back in time and we look at the technical problems found whose solution determines the standards used nowadays. We are in the 1930s, at the beginnings of television broadcasts and cathode Ray Tube televisions: from the CRT design calculations it results that the intensity of the light emitted by the screen is non-linear in comparison to the voltage that controls the electronic brush on the screen, but it follows a relationship known as the gamma function where γ (gamma) is a set value parameter
Displayed brightness ≈ (Voltage corresponding to the original image brightness) γ with γ=2.5
Most of the sensors used in the cameras are already linear, producing output voltages proportional to the image brightness, due to the gamma of the CRT (gamma native) so that the average tones of the displayed images on the TV are too dark, it’ s required to apply a correction to the camera output voltages or to the CRT. Obviously it’s cheaper to correct the defect on a few cameras that send the image to all TVs: when defining TV standards it was decided to add to the cameras a circuit that applies an inverse correction with the parameter gamma set to 1/2.2 (inverse to that of the monitor). In theory the inverse correction should be with the gamma parameter equal to 1/2.5, but it was set to 1/2.2 to balance the apparent reduction in contrast that occurs when watching a TV in a dark room. For a colour TV you need to fix the all the three RGB components gamma function:
Nowadays the computer sends the images to the monitors that are not necessary CRT and plays the role that the camera had for the CRT televisions. Also a monitor built with the new technologies lacks of native linearity to the displayed image color tones and the operating system has to correct the monitor response. At present the operating systems via the video card execute a standard gamma correction set to 1/2.2 as the camera did in the past. In order to avoid that any viewed image is different when viewed on the TV or on the computer monitor, was defined the standard that a display built with any technology has the gamma set to 2.2. For the personal computers the fact is well described in the Charles Poynton’s paper “Frequently Asked Questions about Gamma” of which we bring an excerpt:
BOT_Videocard Gamma Correction
The 24 bit color digitized image is loaded into the graphics card memory (framebuffer) and before sending it to the monitor the video card applies the gamma correction 1/2.2 (0.45) stored in its “Look Up Table”. The LUT is a numerical table that allows to quickly apply the correction to the RGB image components. The video card has two LUTs: the one with a 1/2.2 gamma (which cannot be modified by the user) and the other made available to the user to store the calibration data obtained from the colorimeters/spectrometers. The monitor that receives the image from the computer applies the gamma 2.2 stored in its LUT and so the system displays on the screen the linearized image.
This solves the technological evolution problem for the transmission/reception devices without affecting the images visual perception and allowing the concurrent use of monitors with different technologies: camera manufacturers/operating systems should implement a 1/2.2 gamma correction while monitor manufacturers should implement a 2.2 gamma function. Now the gamma function is no longer a parameter related to CRT technology but a technical specification, in fact a LED technology panel has a native response curve that has nothing in common with a gamma function. Depending on the adopted technology the monitor manufacturers implement appropriate technical solutions to implement this standard.
THE MONITOR QUALITY
In addition to the display technology the quality is also determined by the gamma curve setting.
- What are the defects related to the gamma curve adjustment ?
For convenience we will use a “White Paper” a document in which a producer in response to a problem provides its solution. A “White Paper” is a more commercial than technical document and it’s useful to understand the problem from the user viewpoint. We will use the informations contained in “No.03-003 Rev A” (Eizo) and the Eizo terminology:
BOT_Eizo White Paper
Fig.1 – Monitor Gamma adjustment defects
Fig.2 – Software Calibration and White Point
Fig.3 – Hardware Calibration and White Point
In the Fig.1 we notice that the topic is oriented to the grayscale tones, the reason is that the grayscale tones are colors in which the three RGB components are equal in value, therefore if the 256 grayscale tones are correctly adjusted on the ideal gamma curve will be also the 16 million colors (graph on the right). The monitor calibration (software) by using a colorimeter/spectrometer may be subject to two types of defect:
- Color Seepage
- Tonality Breakup / Banding
Both the defects are related to the 8 bit LUT monitor discretizing: in the natural environment there are endless colors and shades instead for the digital images all the colors are represented by 8 bits for each RGB component. The 16 million colors may seem many but the limit is highlighted by the 256 gray tones which extend from black to white, they cover the entire color range and they require a fine-tuning to the gamma curve which is a continuous curve.
The “Color Seepage” is correlated to the three RGB components of the gray tones that are no longer identical and the mutual difference is such as to be noticed with the presence of other colors in the grayscale tones.
The “Banding” is correlated to the three RGB components of the gray tones that are not so effective in representing linearly the scale tones, flattening the visual perception.
The Fig.2 shows as example the calibration defect (software) correlated to the white point choice at 5000K (the typical factory value is 6500K): the calibration system (software) to lower the white point eventually decreases the value of the single RGB components and in this way the “Color Seepage” and “Banding” defects become visible.
In the Fig.3 the manufacturer shows its calibration (hardware): during the gamma curve implementation it uses more than 8 bit color (for the monitors with 16 bit color, 65536 colors are available for RGB/Tones of Gray or +281474 billion colors) and the monitor LUT is constituted by the 256 RGB component colors that best fit the gamma curve. This is achieved by a purpose-built ASIC circuit. This solution solves the defects related to the white point change and the RGB components can also take on all values from black (0,0,0) to white (255,255,255).
Now that we have a bit better ideas about how the images displayed on the screen should/shouldn’t be, we can start designing our Merkhet-RGB.
We explain in detail the targets:
- At the factory white point display all colors simultaneously and properly
- Change the white point without any colour seepage or banding defects
- PC Configuration
BOT Calibration PC
Fig.1 – Monitor info extracted by EDIDViewer (ELDIM)
Fig.2 – Operating System and Video Card Info
- Hardware Configuration
Monitor: LED LG 20M37A
Video card: Sapphire ATI Radeon HD5770
- Software Configuration
Operating System: Win7 64 Home Edition
Driver Video card: 14.301.1001.0 (Catalyst 14.9)
Application: An image viewer
- Sample Images
As mentioned at the beginning of this article we need a plumb bob and a square, in this case the sample images designed with the proper references to guide the eyes to the monitor calibration.
- What do the sample images look like?
We would like to correctly display all colors so we need the grayscale images to examine the monitor response and the images for the selective adjustment of each RGB component.
- What sort of images should we use ?
The images with shades from black to white (gradient) are useful to identify the color seepage and banding defects but they don’t allow to do much more because the images with gradient or constituted by very thin stripes in strong contrast, after a while that the eyes stare at them, tend to confuse the vision. To aid the view it would use sample images with equal width vertical stripes of a uniform color (grayscale / RGB components) that other than highlighting the above defects allow you to set accurate markers. The grayscale visualization may have the color seepage and banding defects, while the RGB components may just have banding defects. An ideal system displays the different vertical stripes linearly, i.e. without gray tones/RGB components compression/expansion across the entire color range. For a real monitor it’s desired to obtain this result for the grayscale images accepting also some compromises for the single RGB components.
- What markers can we use ?
To display simultaneously all the colors we can create images consisting of gray tones vertical stripes (grayscale) with gray values with step 8 (0,8,16,24,32,40,…,255) and with a more accurate scale with step 4 (0,4,8,12,16,20,…,255). Increasing the accuracy, for example with step 2, you won’t get much more and you would get too close to an uncomfortable gradient effect for our eyes. The same considerations are valid for the three RGB components.
- In what size format do you create the sample images and in what file type do you store them?
We could build the full-screen sample images for 4:3/16:9/23:9 size monitors with stripes of 0.5 cm width for the 17″ (4:3) and 20″ (16:9) monitor so that for larger monitors, such as 48″ (16:9) monitors, they are about 2.5 cm wide for the 8-step sample images and the half for the 4-step sample images.
The file format can be any uncompressed (lossless) as the compression may change the image colors that are the markers for the eyes. We will use the PNG format which takes up a very minimal space amount and allows to store the 24-bit color images.
On the basis of these ideas I built the sample images of which I provide an example:
BOT Sample Images
Fig.1-4 – Step 8 Sample Images for 16:9 monitors
Fig.5-8 – Step 4 Sample Images for 16:9 monitors
Below is the no-logo images complete set for monitor calibrating:
BOT-Monitor-Calibration-Sample-Images.zip (MD5 Hash:dca4e23b993dfd918814508edd80278a)
Overall as the Merkhet of ancient Egypt the sample images are constituted by simple elements (colored stripes) with determined markers (precise color tones) and as the Merkhet the key to everything is is the operating procedure.
- Calibration Procedure
To calibrate the monitor you need to set it to a defined state: set the white point, the luminance and the gamma function arbitrary parameters.
The procedure that uses some basic functionality of video cards is applied by ATI Radeon video card but it’s also valid for nVidia video cards that are equipped with control panels of fully equivalent functionality. The basic features we will use are:
- Color Temperature control (“Monitor Properties” panel tab)
- RGB components Contrast selective control (“Color” panel tab)
- RGB components Brightness selective control (“Color” panel tab)
How to proceed:
Set up the environment under the monitor usual operating conditions and keep on the monitor for about an half hour before starting calibration.
Restore the monitor to the factory settings: each manufacturer according to the monitor characteristics sets the optimal operating parameters that I recommend not to modify.
Use the monitor at the highest resolution defined by the manufacturer: all monitors are designed to obtain the best image quality at this resolution.
Restore the video card to the factory settings: each manufacturer according to the video card characteristics sets the optimal operating parameters that I recommend not to modify.
Disable any calibration profiles generated by the operating system or third party applications: in particular, a generic ICC profile provided for a specific monitor model could improve the images but could also worsen them, so it needs to be verified for example by the sample images indicated above.
By these operations we set the white point at the factory value, the luminance at the factory value that even if higher than 100/120 cd/m2 is fine because the calibration is aimed at viewing the images on the screen and not in printouts, the monitor gamma curve at 2.2 and the video card gamma correction at 0.45 (1/2.2).
Analyze the monitor response using the sample images: It may be useful to start by using the 8-step images and after the monitor calibrating use the 4-step images to obtain a more accurate calibration. By analyzing the grayscale images first and the RGB components next, you can identify the problem that needs to be solved. When the grayscale sample images are properly displayed then the monitor is successfully calibrated.
Adjust the monitor response by the RGB component Contrast selective control and back to the step 6: always remember that lower brightness values allow us to increase the contrast, while higher values can induce you to decrease the contrast. If you don’t remove completely the defects by just the contrast adjustment, after you achieve the best possible settings, go to the step 8.
Adjust the monitor response by the RGB component Brightness selective control and back to the step 6: if there is no colour dominant or a colour seepage defect then it’s better to modify by the same amount the three RGB components brightness, to modify in different amounts the three components brightness beyond some limits can cause a dominant color appearance. Too low/high brightness levels may cause banding defects in the darker/lighter tones respectively.
To calibrate the monitor at a different white point use the Color Temperature control: after you set the new temperature back to the step 6.
This procedure with the guidelines is longer to read than to execute, the key is to have clear how work the brightness and contrast controls applied to the three RGB components.
- Calibration procedure application
I applied this procedure to the 20M37A LG LED monitor for home use purchased about three years ago at the cost of 87€.
- Restore the monitor to the factory settings
Restore the monitor as described by the manufacturer manual: From EDID information the monitor gamma is 2.2 and the white point indicated by the coordinates “White: x=0.313 – y=0.329” is at 6500K (Calculate color temperature (CCT) from CIE 1931 xy coordinates)
- Restore the video card to the factory settings and the monitor at the maximum resolution
BOT monitor LED LG 20M37A 6500K RESET
Fig.1 – Monitor maximum resolution
Fig.2 – White point @6500K
Fig.3 – RGB components reset
Fig.1 shows how to set the maximum resolution for the monitor and its operating frequency.
Fig.2 shows the monitor white point temperature set to 6500K and the Hue, Saturation, Brightness and Contrast parameters set to default.
Without going into the detail, the Hue and Saturation controls are two different ways to enhance or attenuate the color tones. In general, they are of very limited use as they are global, i.e. they act simultaneously on all three RGB components and not selectively. They can be used if the monitor has color tone problems.
In Fig.3, if disabled execute the “Reactivate AMD color controls” and select “All Channels”: the Gamma, Brightness and Contrast parameters for the three RGB components are set to the default ones.
Note: When you restore both AMD and nVidia to the factory settings, they set the “Gamma” parameter to the default value 1.0, this is to denote the video card operating neutral state and not the gamma correction value. Video card manufacturers by the control panels provide the user tools to modify the video card default parameters which, unless otherwise specified, are in arbitrary measure units.
- Monitor response analysis @6500K
In the factory settings we use the sample images (8-step) and in the one in grayscale we can detect the following color seepage and banding defects:
BOT DIFETTI 20M37A
Fig.1 – Grayscale
Fig.2 – Red-scale
Fig.3 – Green-scale
Fig.4 – Blue-scale
In Fig.1 The last 3 stripes have a banding problem with RGB(240,240,240) values and the further 7/8 stripes have a seepage defect with a slight red prevalence.
In Fig.2 The last 3 RED stripes are identical with RGB(240,0,0) values.
In Fig.3 The last 4 GREEN stripes are identical with RGB(0,232,0) values.
In Fig.4 The last 3 BLUE stripes are identical with RGB(0,0,240)
The monitor response is linear up to gray value RGB(232,232,232) and if we consider that this is a factory configuration we can say that it works quite well.
- Adjusting the monitor response using the selective Contrast control
At this step, for each RGB component and the matching sample image, we act just by the contrast and we decrease it until the last stripe appears clearly. Selecting the contrast control cursor by the mouse-click, with the left/right arrows we can decrease/increase the RGB components contrast, we increase the contrast until we see the stripes gradually “disappear” and we decrease it until we see them gradually “reappear” until the last stripe. Thanks to this little trick the adjustment becomes very easy. Using these sample images you perform a preliminary contrast adjustment and after you check the result by the grayscale sample image.
After performing this preliminary adjustment we use the 4-step sample images for greater accuracy and we obtain a better grayscale display by the following adjustments:
RED component contrast: 85
GREEN component contrast: 75
BLUE component contrast: 85
Adjusting the contrast we fixed the banding defect without monitor response linearity loss, but there is still a slight seepage defect for the red component.
- Adjusting the monitor response using the selective Brightness control
By the 4-step grayscale sample image we decrease the red component brightness until it disappears without introducing other dominant colors. Decreasing the brightness accentuates the darker tones and introduces a banding defect towards to the black color, but now we can increase the RED component contrast (to the 90 value). Once we get an optimal result we also check how we see the red component sample image. With the following brightness adjustments we got the grayscale sample image without red dominant:
RED component brightness: -10
GREEN component brightness: 0
BLUE component brightness : 0
Adjusting the brightness we fixed the seepage defect without monitor response linearity loss.
At the factory settings we successfully calibrated the monitor fixing the seepage and banding defects by the following configuration parameters:
BOT monitor LED LG 20M37A 6500K CALIBRATION
Fig.1 – White point @6500K
Fig.2 – RED component configuration
Fig.3 – GREEN component configuration
Fig.4 – BLUE component configuration
Starting from this configuration now we calibrate the monitor at a warmer white point.
- Monitor response analysis @5000K
We set the white point to 5000K and display the 4-step grayscale sample image, the grayscale isn’t too linear and it’s splashed with a pink tint (color seepage defect). By the trick of increasing/decreasing the three RGB components contrast we investigate what happened by the respective color tone scales:
- The RED component has too HIGH Contrast
- The GREEN component has too LOW Contrast
- The BLUE component has too LOW Contrast
This time the seepage defect appears because the RED component has a too high contrast compared to the GREEN/BLUE components, which due to a too low contrast have also the defect of decreasing the image overall brightness. If the contrast is too high the higher red tones, unbalanced in comparison to the GREEN/BLUE components, you notice starting from 2/3 of the grayscale. After the RGB components contrast fixing the grayscale sample image is properly displayed:
BOT monitor LED LG 20M37A 5000K CALIBRATION
Fig.1 – White point @5000K
Fig.2 – RED component configuration
Fig.3 – GREEN component configuration
Fig.4 – BLUE component configuration
We successfully calibrated the monitor at the 5000k white point fixing the seepage defect by adjusting the three RGB components contrast.
Note: I tried to invert the fixing operations, i.e. decreasing first the RED component brightness and after adjusting the RGB components contrast. The result is that as the RED component brightness decreases, this component seepage defect decreases but a BLUE seepage defect appears in the darker tones area and the monitor lacks of linearity to the black color, the first 6/7 grayscale stripes (24/28 tones) are indistinguishable.
In conclusion we successfully calibrated the cheap home monitor LED LG 20M37A at both 6500K and 5000K. 😉
We saw how the seepage and banding defects are depending both on the contrast and on the brightness of the single RGB components. Using these sample images and this procedure, with the defect-fixing due to the contrast before and to the brightness after, we obtain a sort of double “sieve” which minimizes the number of steps required to adjust the monitor as it allows an easier detection of its limitations.
Can we claim that we transformed a home monitor into a professional one?
Thanks to the Merkhet-RGB and a sample images accurate analysis we can adjust the monitor to get the best that the hardware allows. The advantage is that we use these sample images to calibrate the monitor and if they are properly displayed they show the proper adjustment. Furthermore at any time in a few seconds we can verify the monitor for any chromaticity anomalies and if needed remedy them.
To calibrate a monitor equipped with an 8-bit color LUT and internally driven by just 8-bit color you can use the best photometer with the best software and in the best possible way, but the results you get may not be of the best. Just the professional monitors are equipped with hardware that internally handles the LUT with 10/16 bit color and are sold already individually calibrated. From this tutorial perspective may be interesting to use these sample images to verify the monitor calibration performed by the photometer/colorimeter and compare the results with those obtained by your eyes. The sample images thus designed provide a sufficiently objective feedback independent from the monitor calibration method.
Never as in this context it really can be said that the images beauty is in the eye of the beholder! 😀
If you discovered this article useful or interesting we invite you to put in your browser a link to this website full of information and tests carried out by people who motivated by passion spend many hours working on.
Charles A. Poynton Official Website
Robert W. Berger “Why Do Images Appear Darker on Some Displays?”, An Explanation of Monitor Gamma
Eizo White Paper “No.03-003 Rev A”, LCD Monitors for High-End Grafics, (October 16,2003), Eizo Nanao Corporation
ELDIM – “EDIDViewer”, EDID Viewer extracts & analyses EDID data from your windows registry, Freeware
eNJoy aND STay TuNeD WiTH uS!
Raffaele “MOS” Sanapo
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