When an individual views an object, the pupils of the eye are constantly adjusting to manage the incoming light so that each aspect of the object can be seen optimally. The pupil is optimizing the lighting associated with each nuance of the object. It's as if the object were being viewed repeatedly and continuously.

A picture seldom resembles what one remembers having seen 'in his mind's eye' because the camera captures the image of an object from one angle, with the lighting available only from that angle at one precise moment in time. Thus, a photo is the result of one unique and limited aperture and shutter setting.

The Athentech Imaging Perfectly Clear process treats each 'pixel' in a photograph as if that pixel were produced by its own camera. The process treats millions of pixels as if they were the result of millions of distinct cameras, each taking a picture of their one single minute portion of the object – each focusing upon their portion of the object in the optimized fashion.

The Perfectly Clear process then optimizes all of these single pixel 'mini-photos' as if each dot had been exposed with optimal light and with each color being true to "the real world" as seen by the human eye. All this is done within the dynamic range of the whole photograph, meaning it provides a true appearance with zero clipping and zero artifacts therefore resembling the real object with its true color.

This process replicates what the viewer was seeing in 'their minds eye'. It results in a more complete, balanced image, one that is replicated without the loss of important detail and color typical of existing methods.

The keys to Perfectly Clear’s results are the handling of lighting for each pixel and the methodology of maintaining true color, with zero clipping and zero artifacts.

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EXAMPLE OF THE PRINCIPLE OF EACH PIXEL ACTING AS A SEPARATE LENS

The following example shows the concept of each pixel operating as a separate lens. This enables optimal lighting for every pixel in a picture. Imagine that every picture is made up of millions of minute pictures (i.e. - pixels). Each minute picture could be a different distance from the camera and exhibit nuances of lighting challenges. The human pupil continually adjusts to decipher these nuances and by Perfectly Clear adjusting every pixel it approximates what the human pupil does.

The human pupil manages the key aspect of vision, that of gathering light. Photography’s largest challenge is light gathering and that’s what Perfectly Clear does best.

If a picture consisted of only one dot (see below diagram), it would be easy to capture its true color and the optimal lighting condition.

However, in the real world, images consist of millions of pixels , and the dots are all different colors. The challenge in photography is that the bright pixels and the dark pixels are captured with only one lens setting. This means choices must be made.

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.

Until the Perfectly Clear science was invented, the industry “solution” has been to use sophisticated computer software enhancement programs to enhance the photo. This enhancement process can become iterative and entail multiple steps as we’ll illustrate using 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.

The Ideal Case
Perfectly Clear is science that adjusts the color and lighting of each dot as if each dot had its own separate lens setting with a super smart computer adjusting all the apertures separately for the perfect result – true color and optimal lighting every time. The image below shows the results of Perfectly Clear being applied to the original model image which is also represented here for easy comparison.

Perfectly Clear has adjusted the blue, green and brown dots on the right side and the bottom of the model. Note that since the four dots in the upper left hand corner are nearly or properly exposed, Perfectly Clear has made minor or no corrections to these respective dots. The result is an image true to the real world, with true color and optimal light with zero clipping and no artifacts, as seen by the human eye.

Perfectly Clear is designed to deliver the benefits of digital technology – more information per pixel utilized optimally. As cameras and imaging devices increase pixels, and improve imaging sensors, Perfectly Clear gets better too. As you optimize what a pixel “sees”, so do we.

For an example of Perfectly Clear true color rendition, please read on.

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TRUE COLOR EXAMPLE

The following example will illustrate how Perfectly Clear always stays the course on that principle which is critical to good image capture – maintaining true color.

The following image represents dots taken at different exposures (i.e. - apertures and shutter speed) of a camera. As we move from left to right, more light passes through the camera, thus the camera has more light gathering power, and the dots are more vibrant in color. The dot on the left is how cameras frequently capture green grass. Unfortunately, it doesn’t look very green or healthy. The dots closer to the middle and right better represent what healthy grass looks like in sunlight, and how the photographer saw it when he was looking through the viewfinder.

To illustrate the true color principle, we’ve processed the original dot with the world’s leading competitive image enhancement "solutions". As shown below, these "solutions" actually change the color of the dot – true color is destroyed.

Enhancement Solution #1
In this first example, we manually tried to achieve true color for each different camera exposure by adjusting numerous controls. This took a long time with the following results:

The brightest dot is nearly white. Grass does not look like any of these dots on a sunny day.

Enhancement Solution #2
We next processed the original dot through a new image enhancement solution that uses complex mathematical relationships to establish color and contrast. It took a long time to process, with the results shown below.

As you can see, this enhancement process is looking for contrast rather than true color and that's why the ring appears along the outside. This enhancement process is actually creating artifacts, because rings appear within the dots, and you’ll note these rings aren’t in the original dot.

We next processed the dot using four more different software enhancement solutions – all of these enhancement solutions feature a one click solution.

Enhancement Solution #3

Enhancement Solution #4

Enhancement Solution #5

Many of the “solutions” shown above add white to an image to brighten it, and then add color to the areas that have been washed out. Many of the enhancement “solutions” are actually looking to change contrast, as shown by the rings around and in the dots. Other solutions use "memory colors" which entails changing the color of your favourite sweater or your garden to what the computer's database thinks it should look like instead of what it really does look like. Many of the solutions create artifacts which don’t exist in the original image. None of these problems occur with Perfectly Clear.

In order to demonstrate the robustness of Perfectly Clear’s true color solution and in order to contrast its capability with the other six enhancement solutions shown above, we next processed the original dot with Perfectly Clear three times. Notice how the true color remains in the image. In fact, Perfectly Clear "restores" the dot to the same vibrancy as if taken with a camera with the correct exposure (shown below again for comparison).

In conclusion, Perfectly Clear reveals the true color hidden by the darkness – like cleaning a dirty windshield. Perfectly Clear produces the same color as a camera will do when the camera gathers more light.

This principle of true color is applied throughout the entire Perfectly Clear pipeline. Whether Perfectly Clear is correcting for underexposure, removing abnormal tint, restoring color, or applying our medical quality contrast and sharpening, true color is always maintained with zero clipping and zero artifacts. 

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