Posts Tagged ‘image enhancement’

Color adjustments : brightness, contrast and gamma

Hi folks,

Today we are going to explain some terms related to color adjustments in digital images because all our products provide such features and since some have “esoteric” names (such as “gamma”) our general public might skip using them at image quality enhancement time.

Brightness and contrast are very well known image adjustments but let’s mention them nevertheless :

- Brightness reffers to the absolute value of colors (tones) lightness/darkness.
Increasing brightness of an image will light out all colours so the original light ones will become up to white.
Reversely, decreasing brightness will darken all colours so the original shaded ones will become up to black.

- Contrast  is about the distinction between lighter and darker areas of an image and it reffers to making more obvious the objects or details within an image.
Increasing contrast on an image will increase the difference between light and dark areas so light areas will become lighter and dark areas will become darker.
Reversely, decreasing the contrast will make lighter and darker areas stay approximately the same but the overall image becomes more “flat” and starts looking as if it were “washed out”.

- Gamma correction is not just as easy to understand and here is why: there is an important difference between how human eye perceives light compared to how image-capturing devices do (cameras, scanners, etc).
Digital image-capturing devices work based on a simple rule : if twice the photons hit a sensor then twice the signal will be generated.
Eyes don’t work the same way, as biology is almost never governed by linear simplicity : we are more sensible in perceiving changes occuring in dark tones than similar changes occuring in light tones.
When our eyes receive twice the photons, the visual sensation is not that of twice the brightness, it depends on the context so linearity here is an exception instead of a rule.

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Image enhancement : median filtering

Hi folks,

We continue the series of explanations on image enhancement techniques meant for our general public and this week we are going to give you some additional info about median filtering.

Images quite often contain artifacts known as “noise”.
“Noise” means, of course, un-wanted sounds occuring in an audition context but the term quickly expanded to other domains, designating the presence of un-wanted randomly disseminated artifacts within any given context.
In imaging domain, for instance, one of the frequently occuring noise-types is called “salt and pepper noise”.
Quite an intuitive name, as images affected by this type of noise look like as if salt and pepper particles were poured over “the clear” image (bright pixels on darker areas and dark pixels on brighter areas of the image).
The usual causes for this issue are hardware related (analog-to-digital conversion, bit errors in transmissions, etc.).

Which brings us to the median filtering : one of the most effective method to remove such noise from images is to apply the median filter.

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Deskew/Autodeskew : what’s that ?

Hi folks,

This week we thought about offering to our general public some explanations about deskew/autodeskew, mainly to answer two questions : what’s that and why is it important to have ?

Skew is an artifact that might appear during document scaning process and it consists of getting the document’s text/images be rotated at a slight angle.
It can have various causes but the most common is paper getting misplaced during scan.
Therefore, deskew is the process of detecting and fixing this issue on scanned files (ie, bitmap) so deskewed images will have the text/images correctly and horizontally alligned.

And why is this important ?
Well, a first benefit will be that you don’t have to scan in again the skewed documents.
Instead of the mechanical and time consuming actions that re-scan involves, everything is done automatically and efficiently by the software providing deskew feature.

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