PART A -- Perfectly Clear Photo Corrections

• CHAPTER 1 -- Full Spectrum RGB
• CHAPTER 2 -- Perfect Exposure
• CHAPTER 3 -- Vibrancy Correction
• CHAPTER 4 -- Tint Correction and White Balance
• CHAPTER 5 -- Contrast Correction
• CHAPTER 6 -- Sharpness Correction
• CHAPTER 7 -- Red Eye Correction
• CHAPTER 8 -- Noise Reduction
• CHAPTER 9 -- Skin Tone Adjustments 1 - Automatic Removal of the Infra Red
• CHAPTER 10 -- Skin Tone Adjustments 2 - Skin Tones for your Culture
• CHAPTER 11 -- Portrait Light Diffusion
• CHAPTER 12 -- Vivid Full Spectrum RGB

 

CHAPTER 1 -- Full Spectrum RGB

Have you noticed how the colors from your digital camera are distorted?

Point your digital camera at a purple object. Compare the image in the view finder with the original purple object in front of you. Often the image of the blue object on screen will be different from the purple (Fedex box or purple bride’s maid dress for example) object itself, as shown in the following figure:



The first step in removing color distortion is to overcome the limited RGB spectrum of your camera. Digital cameras do NOT reproduce colors the way the human eye sees them.

This is because your eyes see this spectrum:              but most cameras see this spectrum:
                                                  

Although the distortion is across the entire color spectrum, it’s particularly noticeable in the greens and in the higher frequencies of indigo, purple and violet, as shown in the below photos.

Before - Very lacking in color and vibrancy                   After - Notice how the greens and purples are much more vibrant

Most digital cameras employ an abbreviated color spectrum because of how the RGB color space is defined and implemented.  Perfectly Clear provides the only solution for accurate colors in your photos.

Your eyes see the full spectrum of visual light. Most cameras see a more limited spectrum, which is one of the 15 Ways Your Camera Distorts Color. This means the colors of your photos are distorted so they don’t match the colors of the original image of the event in your minds eye.  Science shows inaccurate Photos have low emotional impact because they’re insufficient memory triggers to re-ignite the Precious Memory you’re looking to preserve. So why does your camera see the more limited spectrum and produce the image on the left, when your human eyes see - and Perfectly Clear creates - the spectrum and image on the right?

Simply looking at the image and their two spectrums tells you digital cameras are NOT reproducing colors the way the human eye sees them. This is a vitally important observation because we know colors are like an express train into the Precious Memories of the human brain.  Science has shown that when you distort color you distort the Precious Memories, which is why Photo Accuracy is so important.

When you and those you’re taking photos for want to re-experience your Precious memories perfectly, then those memories need to be perfectly preserved.

How can a Precious Memory be perfectly preserved if the colors are changed?

We know that the cones of the human eye respond with precision to the frequencies of specific colors.  And each color detected by the cone cells of the human eye creates a very specific electrical and chemical response in the brain.

CIE 1931 Colour matching functions for 2° observer

The image formed and then stored as the original image in the mind’s eye of the human brain is a result of these electrical and chemical responses generating wave response.

When your camera changes the colors of what you see (the original image of what you see and store in your mind’s eye), and when your photo “enhancement” software distorts the colors of your images, then the Precious Memories represented by your photos will be distorted. Your wife’s favorite sweater is no longer the same color.  How should we expect her to respond upon seeing the color of her sweater distorted?  What if it’s the color of someone’s eyes that are distorted?

Original                                                                                           Perfectly Clear

Perfect color – Real Color – means a perfect reproduction of the colors you see and seek to capture in your photos.  Perfect color means perfect Precious Memories; therefore, Real Color means perfect preservation of Precious Memories. To reproduce and preserve Precious Memories perfectly, the colors seen when the picture is taken have to be reproduced perfectly in your photos.  Only then is your photo reproducing the original image of the event in the mind’s eye and having the maximum emotional impact.

We’d be pleased if you’d participate in an experiment with us and point your camera at the screen.  What color do you see?

One of two things just happened, either:

1. Your camera wrongly rendered the purple woman as blue, or
2. Your camera correctly rendered the woman as purple, and wrongly de-saturated the colors so your photos are going to contain less vibrancy than film.

Which outcome you experience is a result of how your camera manufacturer implemented the RGB standard.  How do we know this?

Cameras utilize the RGB color space.  In 1931 the RGB color space was defined by the Commission Internationale de l’ Eclairage (“CIE”). The CIE definition included negative numbers in the red channel.  This does NOT represent negative light, but it’s a convenient way to represent that there’ll be situations where the color red has to be added to the color being matched, and not to the mixture. Red cone cells do actually have a response to high frequencies [in the blue range]. As surprising as this is, this response had to be included in the RGB definition. So how does a camera manufacturer implement negative numbers?  They can’t! So the manufacturer only has two choices:

• apply a brute force logic to the RGB definition and set the negative numbers to zero.  This abbreviates the spectrum in which case the purple in the blue end of the camera’s spectrum remains perfectly blue, and the green/turquoise portion of the spectrum is changed even more significantly (although it won’t be noticed by the novice eye as quickly), or

• adjust the camera’s RGB color spectrum with differing amounts of de-saturation (adding some amounts of white).  This is done in a genuine attempt to approximate the natural fuller spectra, but the de-saturation will always be present.  De-saturation reduces the vibrancy of your photos. For further information on  samples of the de-saturation required to achieve all the hues of the spectrum, please go to http://www.techmind.org/colour/spectra.html.

Application of Full Spectrum RGB technology reproduces your photos with the vibrant colors you see (original image) at the time you take the picture.  This is going to include the many complex greens and even those high frequency difficult hues such as the deep indigo, violets and purples.




Full Spectrum RGB is a digital color model based upon the full color spectrum of natural light.
Full Spectrum RGB uses digital light to simulate the dynamic nature and depth of the component colors of daylight.

You use your digital camera to record light and your monitor displays images using light.  But the light you record with your camera and the light created by your monitor are different.  They have different component colors, and the component colors of the two systems interact differently. Daylight contains all the visible wavelengths of illumination.  The human eye perceives discrete wavelengths as colors.  We commonly classify the component colors of the visible spectrum as red, orange, yellow, green, blue, indigo and violet. Digital light simulates white light with only three individual wavelengths of color:  red, green and blue (which is why the digital color model is referred to as RGB). The differences between daylight and digital light can be seen in the purity of their respective component colors.


Perfectly Clear incorporates Full Spectrum RGB to give your photos the benefit of the fidelity of all the colors that were present at the time of capture, an imperative to accurately reproduce the colors of your photos.  Real Color.

Original                                                                                           Perfectly Clear

Of course, it’s possible your camera manufacturer chose to not slave the negative numbers to zero, in which case they will have added white to the spectrum to simulate a full spectrum.  This is overviewed in the discussion of this camera limitation.  The result is that the photos from such camera lack crisp vibrancy. Another reason photo colors can lack vibrancy is caused by another camera limitation where the camera tries to overcome an exposure problem.  In either of these cases the solution wouldn’t be Full Spectrum RGB, but rather Perfectly Clear’s Vibrancy correction.

Delivering you accurate photos with optimum exposure, detail preservation and correct colors… Real Color, is absolutely necessary to reproduce your photos to match the original images stored in the mind’s eyes of the photographer and participants.

Accurate Photos are Superior Photos that preserve Precious Memories better and have the greatest emotional impact on the viewer.

CHAPTER 2 -- Perfect Exposure

Improper exposure in any portion of your photos results in color distortion and disappointment.

It’s probably fair to say that the biggest challenge in photography is trying to get perfect exposure throughout every aspect of your entire photo.  This is because of the camera’s inability to reproduce what the human eye sees.  The human eye is dynamically adjusting for exposure – whereas the camera only contains a single aperture.



Even in a great photo, some portion will be improperly exposed relative to what the eye sees.  Inaccurate exposure means inaccurate lighting - and inaccurate lighting means distorted colors. 

Compounding this is the traditional method used to increase brightness - adjusting Luminance – which guarantees even further color distortion.

Perfectly Clear is the only solution that emulates in your photos the essential and correct missing eye function the camera lacks, while rigorously adhering to the physics principles of light.  The result is Superior Photos and superior emotional impact on those who view your photos.

Statistical studies have shown that as many as 90% of all photos taken have some sort of exposure challenges.  Is this because the photographer taking the pictures is incompetent?  Absolutely not.  It’s simply a result of one of the 15 ways your camera distorts color.

The challenge with exposure is intrinsic to camera design and has been from the beginning of photography.  There’ll always be endemic exposure challenges as long as cameras have a single aperture and shutter settings. It’s impossible for a single aperture to open and close in a precise instant and properly expose everything in a photo.  Photos include subjects/objects at different focal distances. Each often exposed to different amounts of light.  Even the character of the light they’re exposed to could be different. How can a single aperture with a single shutter speed accurately represent this diverse information? 

The camera operator, knowing the limitation of his single aperture, focuses the aperture on a particular subject/object in the photo and selects a unique shutter setting.



Although this is perfect behavior, the result of these actions means that some portion of the photo will be properly exposed and other parts not. So exposure in photography, digital or film camera, is a compromise.

 

This is the problem

The insurmountable challenge for the camera is that single aperture means that the camera has a fixed and restricted dynamic range. But the advantage of digital over film is that poor exposure can be overcome after the fact.

The iris - the eyes equivalent of the aperture, is constantly adjusting itself to optimally expose the object that has caught your interest (the current subject). As you’re looking around, your eye’s irises are adjusting to optimally expose objects that catch your interest. The dynamic adjusting of the dynamic range of your eyes means everything that catches your focus is recorded with the equivalent of a good exposure setting.

The eye

These continual focal adjustments are why your eyes see an event differently than your camera does. Your eyes are actually seeing the event over a period of time. Your eyes are literally sending thousands of images to the brain to render a composite – and thorough – original image of the original event in the mind’s eye.  In effect, unlike the fixed dynamic range of the camera your human eye is dynamically making ongoing dynamic range adjustments to see everything clearly.

Perfect Exposure for a Superior Photo means optimal light intensity, or, in other words, optimal exposure, in each and every pixel.  A Perfect Exposure photo correction requires:

1. optimally increasing the light intensity in every pixel in a manner consistent with the physics principles of how the human eye gathers light so all color attributes are responding to the natural attributes of increasing light, and
2. preservation of Real Color, the original hue of all of the colors in the photo with a patented approach to the RGB Triplet, which will best match the colors of the original event.

To achieve these two principles requires an emulation in your photos of the essential and correct missing eye function your camera lacks.

What if you had a lens emulated at every pixel as Perfectly Clear does as shown in this figure?


“This is the patented solution for optimum light gathering”

This patented innovation of emulating a lens at every pixel is an enabler for the solution to analyze light at the pixel level and is a critical piece of Perfectly Clear’s Perfect Exposure. What magic is the solution doing at the pixel level? It’s achieving the two key components necessary to meet the two objectives set out above. Firstly, it’s maintaining the original hue of the color on a pixel by pixel basis. That is, it’s maintaining the hue of each pixel’s location within the CIE color space, by applying a patented RGB Triplet innovation.  This is an integral aspect of accurate color and is covered fully in the section on Real Color. Secondly, it’s addressing the challenge of how color is affected as more light is gathered.  Fundamentally how light is added to a photo, and the impact it has on color is the single most important issue in photography.  To get the accurate outcome Perfectly Clear is modeling the logarithmic function of how the eye gathers light on a pixel by pixel basis, the whole time adhering to the physics principles of incoherent light. Taken together, these produce optimal lighting in every pixel.

The result is a high degree of Photo Accuracy so that your photos are beautiful and match the original image in the mind’s eye.  These have been found to be the best memory triggers of the original Precious Memory. Taken together these actions effectively reproduce in your photos the essential and correct missing eye functions your camera lacks. A Superior Photo has the greatest emotional impact on the viewer.


The common “enhancement” methodologies for addressing exposure/brightness challenges of adding white, changing Luminance, dodging and burning, and memory colors results in clipping,  arbitrary color shifts, washed out photos and distortions.  This example shows the original corrected with a Luminance correction (notice how it’s washed out) and then with Perfectly Clear bringing out the vivid colors with proper exposure.

Some systems resort to memory colors to overcome these obvious shortcomings, but even the software database containing these memory colors frequently fails. This is ironic because they’re supposed to create blue skies and green foliage regardless of the exact hue in the original scene. However, memory colors often turn the blue sky to grey and the underexposed blue water to grey, whereas Perfectly Clear will maintained the vividness of the blue sky and water.  In the example below notice how Perfectly Clear brings out the blue water and whites in the sails and sailboat as they appeared that day whereas the memory approach keeps everything very dull and grey.

A further challenge with memory colors and fuzzy logic is that, although they’re supposed to be like “paint by numbers “, they often don’t get the numbers correct!  You’ll note below how, in an attempt to turn the sky to a darker blue, a large portion of the sky is missed close to the house and the leaves. This creates a glowing “transition zone.”

These distortions occur because these other methods either don’t model any eye function or, if they do, they model the wrong eye function. Learn more about how todays editing and “enhancement” software takes your Camera’s Distortions and adds “Enhancement” Software Distortions.

Perfectly Clear overcomes your camera’s limitation of poor exposure and lighting in your photos, a very common problem of digital cameras.  Unlike other photo “enhancements”, the Perfectly Clear correction operates to add light in a natural manner consistent with how the human eye gathers light. This is achieved with a series of algorithms that replace the essential missing eye function the camera lacks. The results are Accurate Photos that match the original image in the mind’s eye and serve to preserve Precious Memories perfectly.  Accurate Photos are Superior Photos and science shows superior photos have the greatest emotional impact with viewers.

 
Combining Real Color with Perfect Exposure reproduces photos with true, accurate colors and, optimum exposure throughout. By correcting two major camera’s limitations [link] significant color distortions [link] are corrected and your photos better match the original image in the mind’s eye.  Photo Accuracy [link] demands Real Color.

 

Inadequate color vibrancy is a form of color distortion (also referred to as “washed out” photos – like a newspaper that has been out in the sun for many years). A common criticism leveled at digital photography is that it lacks the vibrancy of film.  We agree that this is a valid criticism. There’s two reasons digital photos often lack vibrancy.  One’s related to camera manufacturers attempting to overcome the camera’s abbreviated spectrum [link] which is addressed in the section Full Spectrum RGB - Auto Correcting the Abbreviated Spectrum and in this camera limitation. The second cause of insufficient color vibrancy in digital photos is actually related to digital cameras’ “second guessing” the photo’s exposure post interpolation.

When the camera detects the photo it has taken is imperfectly exposed, an “if/then” statement in the camera’s software algorithms tells the camera to brighten the image.  The results are photos that are lacking in color vibrancy and thus not eye pleasing or accurate.  Read more to find out how Perfectly Clear automatically corrects this.

Original                                                                                             Perfectly Clear


Many photos taken with digital cameras become washed out or lack color vibrancy because the “smarts” of the camera are attempting to overcome a generalized exposure problem.

This is a valid reason for many photographers to hang onto their film cameras. Silver halide is particularly strong at maintaining color vibrancy in images.  But then, of course, film cameras didn’t have the opportunity to “second guess” the exposure that had already been recorded on the film!

So a funny thing happened on the way to the forum…

Your camera accurately detects the original photo its captured is generally underexposed.  Its identified a legitimate problem. The software contained in the camera’s Digital Sensory Processor [DSP] has an “if/then” statement that tells it to brighten the entire image.  This is done with a Luminance “enhancement” which algorithm brightens the photo by adding white throughout the photo. White, even in small amounts, reduces the vibrancy of the photo and shifts the original colors arbitrarily. Luminance models the wrong eye function and when you examine the history of Luminance it’s shown that it wasn’t developed for photography.  An example of the negative impact a Luminance correction has is shown here.

“Enhancing” a washed out photo engages you in a circle of dependent controls with your software editing tools. For example, you notice your photo lacks vibrancy. It’s washed out from your camera increasing brightness, so you upload it into your photo editing/”enhancement “software to work on it.  A natural approach to addressing the apparent lack of vibrancy would be to select a tool within your software to increase color saturation. Today’s software tools increase saturation by applying the saturation increase throughout your entire photo.  Although this is industry practice it’s unnatural as to how the eye behaves and how the eye gathers light.

The human eyes aren’t rigid.  Vision itself requires eye movement.  As your eyes are viewing a scene they’re continually adjusting their dynamic range to see things clearly. This means the original image of the event in your mind’s eye has discerned different levels of saturation.  Any proper saturation increase needs to be disproportionate to reflect how our eyes are gathering light. Any general increase in saturation is therefore completely arbitrary and has nothing to do with how your eyes would have responded. Because the increase is general throughout the photo it’ll often also lead to clipping of data in the darker areas of your photo. To combat your software’s unnatural saturation shift, and the resulting color distortion, you may have to try to modify the hues.  Now you’ve moved from your photo “enhancement” software distorting your colors to you doing it consciously. The distortion builds and cascades, all because your photo software doesn’t model the reality of how the eye works.

To illustrate these choices, we’ve designed a model. We will illustrate the challenges of enhancing a “photo” taken with a single lens and the impact that each choice has. The model consists of 3 blue dots (representing the sky), two green dots (grass) and four brown dots (earth).

Option #1 – Darkness
The first choice is to error in favor of darkness. This results in the darkest dots being difficult to see as shown in our model above. Only two of the blue dots and one of the green dots are properly exposed. The rest have been captured with too little light. It is like grass in the shade – in the real world it appears brilliant, but on the photograph it appears dull.

Option #2 – Brightness
A second option would be to error on the side of brightness. The dots that were dark in the above example will now be brighter but we’ll lose both the bright dots and the ones that were previously properly exposed. You’ll see the brightest dots have now become white. This is not a true reflection of sky, grass, or earth, and not what the photographer saw in the real world. The results of applying this option are illustrated in the following iteration of our model.

Increasing Brightness
Firstly, in order to correct for the dark dots, the brightness would be increased. Increasing the brightness affects the whole photo, unless the user brightens each pixel, which is not practical. The result is an image that looks all faded. Additionally, the color has been changed – the previously correctly exposed brown and green dots are now a faded yellow. This definitely is not a true reflection of what the photographer saw in the real world. Note below how our model is faded and the brown and green dots are changing color.

Increasing Saturation
Since the photo is now faded, the second step is a step to increase the “color”, (commonly called saturation) of the photo. This is the same as adjusting the color controls on old color TV’s. We’ve now undertaken the process known as color correction, which process requires a talented person who has knowledge of color. As the image of our model below shows, increasing the saturation makes all the colors vibrant again, but this has sacrificed true color. In fact, one green and brown dot that were correctly exposed initially, are now a brilliant yellow. This isn’t even close to what the photographer saw in the real world.

Increasing Hue
The third step in color correction could be to use the hue control to try to bring the colors back to their true color. Our model below shows what a hue correction of 50 degrees does. Again, the whole image is affected. One could argue that this correction almost brings back the correct color in the sky (blue dots) and the grass (green dots), but the earth (brown dots) are now an olive color. Again, this is not what the photographer saw in the real world.

What else could be done to correct this image? We could start the process over again, changing the different controls forever. It’s our experience that once some of the dots are damaged there’s no way to restore them perfectly, and there is no way of restoring them approximately without damaging the other dots.

If we could build a smart camera that had a lens for every dot, then we could capture each dot in a perfect way – true color and optimal light.

In real life, to see all aspects of a scene more clearly your iris is dynamically adjusting to gather different amounts of light in different parts of the scene. In effect the light is increasing throughout the image in differing amounts from location to location, and so will the saturation. The brightness and saturation increases need to vary relative to the darkness or brightness of a given pixel.  The human eye will automatically increase its dynamic range to see the darker areas more clearly and much less in the brighter areas. The key is a proper photo correction must improve your photo by emulating how the irises of your eyes are constantly adjusting and only then will your photo better reflect the original image of the event in the mind’s eye.

The problem is the “vicious circle” results from using a suite of approximate solutions, often involving individual color channels, as opposed to one nice “reasonably exact” solution. The challenges the vicious circle presents manifests in having to spend hours to learn various software tools to deal with the problem, having to spend time applying that knowledge to “enhance” your specific photo, and, your photo moving further and further away from what the eye witnessed of the original event.  Because distortion is the order of the day you’re moving further and further from Photo Accuracy and matching the original images in the mind’s eye.

Perfectly Clear automatically detects a lack of vibrancy in your photos and corrects it by:

• detecting the arbitrary amount of white the camera has added to brighten the image,
• removing the white to return the image to the original colors, and improper exposure,
• applying Full Spectrum RGB to accurately re-map the colors
• applying Perfect Exposure to improve the exposure in a natural way like the human eye while retaining the accurate color, the Real Colors, 
• boosting the colors in a patented manner that emulates how the eye adjusts saturation on a pixel by pixel basis, relative to the brightness of each pixel, thereby maintaining  the accurate color relationships

Original                                                                                                    Perfectly Clear

When Perfectly Clear provides manual ‘tweaking” controls, such as in Perfectly Clear Pro Software, the control is an “independent” control. The power of the Perfectly Clear correction is that it recognizes the truism:
 

This honors the truism by adjusting the saturation relative to the light of each pixel on a pixel by pixel basis with dark pixels receiving light and saturation disproportionately to the increase in brightness and saturation for a bright pixel.  Therefore, the Perfectly Clear vibrancy correction is NOT an averaged adjustment (‘filter equivalent’) applied to your entire photo.

As you can see in the below examples, Perfectly Clear will brings out the lacking color vibrancy, whereas other automatic solutions will keep the colors washed out, or make them even worse!

OriginalCompetitorPerfectly Clear

The beautiful and accurate corrections of Perfectly Clear is the sort of thing that “getting the physics right” can do for you.

Original                                                                        Competitor                                                               Perfectly Clear

The Vibrancy Correction in Perfectly Clear is constrained by the patented invention of Perfect Exposure [link] which limits light adjustments to the physics principles of how the eye gathers light ensuring that the correction reproduces photos with true, accurate colors …  Real Color.

Perfectly Clear overcomes your camera’s limitation of washing out or reducing the vibrancy of your photos, a very common problem of digital cameras.  Unlike other photo “enhancements”, the Perfectly Clear correction operates to add vibrancy in a manner consistent with how the human eye gathers light. This includes replacing the essential missing eye function the camera lacks.

The results are Accurate Photos that match the original image in the mind’s eye and serve to preserve Precious Memories perfectly.  Accurate Photos are Superior Photos and science shows superior photos have the greatest emotional impact with viewers.

Abnormal tints destroy the colors of your photos and results from a camera limitation associated with white balancing.

With all the high tech science in today’s digital cameras, how is it you still sometimes get these abnormal tints?  How come the colors in your photos aren’t true to what you see when taking the image?

Light is fundamental to photography, and, of course, the character and quality of your photo is proportional to the character and quality of the light being captured.  In today’s digital world, the character and quality of the source light captured is automatically determined by your camera.

The challenge is your camera can be exposed to multiple light sources simultaneously. In this situation how does your camera choose, which is the primary source light it should use to compute its white balance?  If it chooses incorrectly your photo most certainly will not match the photo opportunity you set out to capture.

There’s a solution.

Digital cameras have an advantage over film because they can compute a digital white balance.  What this means is they determine the primary source light for your photos and use the white color in your photo to compute a color balance to match the light source they’ve chosen. However, when your camera incorrectly identifies the light source for your photo, color distortion is guaranteed. If the incorrectly identified light source results in a significant color shift, the severe color shift is called an abnormal tint.

After the camera has determined the primary source of lighting, what science does it use to compute its white balance? White balancing is based upon applying the principles of Black Body Radiation theory. Black Body Radiation theory postulates that color frequencies can be exactly matched to a specific temperature.  This can be a camera limitation that results in distorted color so we cover the subject fully here: 15 Ways Your Camera Distorts Color: Camera Automatic Function of White Balancing. In short, the accuracy of the color in your photos is dependent upon your camera assigning an accurate temperature representative of the qualities of the type of light in your photo.  The accuracy of the temperature is important because all colors in your photo will be rebalanced by your camera using what it selects as the reference temperature for the source light. A camera is challenged with a significant number of variables when a picture is being taken but none greater than distinguishing the source of the light present. 

To determine what type of light source is present in your photo the software of your camera searches your image for some representative white (or gray) color. 

When such a color is identified:

• the temperature of the light for that white is estimated,
• the identified white is assumed to be pure white and its temperature is then recast at 6500 degrees Kelvin, presumably because white is considered pure white at this temperature,
• differential calculations for shifting the representative white (estimated color temperature) to pure white at 6500K are then applied to “rebalance” all colors in your entire photo.

The rebalancing of all colors from a known white is consistent with Black Body Radiation theory, because all colors will be on the same temperature curve - see 15 Ways Your Camera Distorts Color: Camera’s Automatic Function of White Balancing.

There are however at least four challenges with this approach:

1. Often the camera’s algorithm selects a non-representative white and then re-balances all the colors in the photo based upon the temperature of this non-representative white;
2. Sometimes there’s no white in the photo and the algorithm selects a non-white color to determine the temperature from which to re-balance the photo, 
3. The camera selects the brightest color value as white; or 
4. Even if the algorithm selects an appropriate white from which to balance some portion of the photo, the re-balancing is being done throughout the entire photo, and

…these challenges, as stated here, really oversimplify the reality the camera is facing.

The quality and sources of light present in your photos can vary widely: ranging across a broad spectrum from direct sunlight, skylight, and cloudy situations, to moonlight and artificial lighting conditions such as fluorescent and tungsten lighting and more. Most importantly, there’s often several different light sources present when a photo is being taken. A night photo could have, for example, a combination of moonlight, sodium vapor street lamps and an automatic flash.  Which temperature does your camera choose as the representative light source?

Or imagine a sunset in the mountains where a mountain casts a long shadow across a huge expanse of trees.  In this case:

• you’ve got reddish light from the sun which is represented by one temperature, being a cool Kelvin temperature, (although we think of the color as warm),
• you’ve got a greenish light from the trees which could be represented by a mid level Kelvin temperature, and
• you’ve got a third temperature of light from the shadows, being a hot Kelvin temperature representing the blue end of the spectrum, (a psychologically cool color).

Which temperature does your camera choose as the representative light source?

In the previous two examples there’s really no one correct answer because there can be no single temperature representative of the multiple sources of light present in these photos.  So even if Black Body Radiation Theory were a perfect solution for White Balancing, no camera could ever pick a single perfect temperature curve to represent multiple sources of light in your photos.

Artificial “man made” lights [such as fluorescent and various lighting sources in street lamps such as sodium vapor] discharge light in narrow spectral bands. These light sources tend to be incomplete spectrums that have color “spikes” so the color captured by your camera’s digital sensors won’t be predictable or controllable.


These types of light sources aren’t Black Body Radiation at all.

Because these challenges are known your camera often gives you a number of options to choose from.

 
Today’s cameras give you, usually, three broad ways to manage the white balance challenge; ie determination of the temperature of the representative lighting of your photo:

1. Automatic White Balance - here the camera is going to determine automatically what it believes is the temperature of the representative light.  Given all the variables this often works surprisingly well but we’ll articulate below why it’ll seldom result in an accurate reproduction of the colors you saw at the time.
2. Pre-set White Balance - this option enables you to choose a specific setting that you believe will accurately reflect the light present.  These options are going to usually include sunny, cloudy, shadows, tungsten, fluorescent, flash and night time.  When you make your selection you are, in actuality, making a manual selection of a single Black Body temperature curve.  Your selection will seldom match the circumstances exactly.
3. Custom Setting - this option enables you to use the camera to custom create a white balance.  This is normally done by taking a photo of something gray in the given light conditions which will be used later as a reference.

CHAPTER 9 -- Skin Tone Adjustments 1 - Automatic removal of the Infra Red Effect

A common challenge in digital photography is what we’ll call the over responsiveness of the cameras sensors to a range of long wavelength frequencies unseen by the human eye.

Heat is emitted from people as infra red radiation. Your camera has three color filters which overlay the camera’s sensors: red, green and blue (an exception to this can be Nikon camera’s use of CYM filters and Foveon’s proprietary non-filtered approach).  Infra-red light passes through the red filter and therefore generates a voltage response for the “red” sensor.  As infra-red is not seen by the human eye this voltage response is effectively boosting the “red” channel. This is a camera limitation that is going to result in color distortion. Because the longer wavelengths of light are most often represented in skin tones, this is where the distortion will occur.

Original                                                                         Perfectly Clear

Perfectly Clear will automatically search for and detect excessive red in skin tones and reduce it. In the “after” image note how the skin tones have been reduced but the other reds in the image have been maintained.

The body regulates the rate of heat loss by dilating or constricting blood vessels at the surface of the skin. When our body is hot or is producing excessive heat, as by exercise, exertion or exposure to sunlight, our arteries open up (dilate) and blood comes more to the surface of the skin to release the bodies heat.  This accounts for the reddening or flushing of the skin.

A more prevalent reason for “flushing” of a persons’ complexion, and completely unrelated to working out or excessive heat, is dehydration.  The human brain is 1/50th of our body mass but receives 25% of the blood flow.  The brain is 85% water and when your daily consumption of water is inadequate your brain will demand priority on the water in your system.  Dehydration activates the hormone histamine to ration the water in your system.  The facial flushing is a result of the brain demanding water.  So when you want your skin to fit within the preferred skin tones increase your water (and sea salt) intake!  It’ll take 3 months to rehydrate your body.  We wish you good health!

Skin tones in your photos will have to be balanced between camera sensors capturing to non-visual light, skin tone preferences of what you may prefer skin to look like, and the reality of the human physiology of the moment recorded in the original image. Perfectly Clear allows you the choice of Real Color and your preference.

Abnormal and improper red skin tones are an unwanted color distortion in your photos.  In such a case their effective removal is necessary to reproduce your original experience. The challenge remains that the human eye is a response mechanism recording the actual skin tone color and not that which you might “prefer”.  Better matching of the original image in the mind’s eye requires accurate colors for you to achieve the benefits that an accurate photo delivers.  Photo Accuracy [link] demands Real Color.

Skin tones have been and will continue to be a “sensitive” topic as different countries and cultures have a preference on the specific look of their skin. 
As a result, the Perfectly Clear bias algorithm has the ability to provide you with several different options on the look of your skin tone.  The examples below show how you can create slightly whiter skin tones, or much whiter (as preferred in the Asian cultures).

Original                                                Perfectly Clear with Skin Tone 50%              Perfectly Clear with Skin Tone 100%

Portrait photos are suboptimal when the subjects are exposed to hard lighting situations. Hard lighting is unnatural and results in color distortion. Perfectly Clear applies a process to automatically soften the lighting.  This results in superior Portraits with more accurate color.  More