Welcome to EDIP (Easy Digital Imaging Processing)’s documentation!¶

Contents:

E.D.I.P presentation¶

Program: Edip

Version: 1.0.0

Author: Eddie Brüggemann <mrcyberfighter@gmail.com>

Language: C++

Release: 24/11/2015

License: GPLv3

E.D.I.P the Easy Digital Imaging Processing program¶

Edip is an easy to use image effects processing programme with severals functionnalities.

Edip permit to:

Rotate your image over 90° to the left or to the right.

Mirror your image, so that:

The left side from your image is copy, mirror likewise, on the right side.

The right side from your image is copy, mirror likewise, on the left side.

The upper part of your image is copy, mirror likewise, on the bottom part.

The bottom part of your image is copy, mirror likewise, on the upper part.

Zoom on a selected center or the default image center.

Flipping your image.

From left to right.

From right to left.

From up to down.

From down to up.

Edip permit to change the image color intensity and some phenomenal color spaces settings.

Color intensity

You can set the red intensity.

You can set the green intensity.

You can set the blue intensity.

You can set the global intensity.

Phenomenal color spaces settings

You can set the Lightness from your image.

You can set the Hue from your image.

You can set the Saturation from your image.

You can set the Brightness from your image.

Edip permit to apply severals built-in filters to your image by simply selecting the wanted filter in the list and pressing the apply button.

The built-in filters are divide into 3 differents categories:

normal filters

You can apply over 30 differents filters to your image.

Grayscaling filters

You can grayscale your image according 6 differents algorithms.

Colorscaling filters

You can colorscale your image in 6 differents colors (red, green, blue, yellow, pink, turquoise) according differents algorithms for every color.

In addition Edip provide many fully configurable filters which you can apply to your image:

Kernel filters.

Photography filters.

Morphological filters.

Canny filter.

Color contours filter.

Multiply colors.

Multiply global intensity.

Set image in color tone.

Edip provide some basic draw functionalities to draw onto your image in the wanted color with the wanted thickness or to fill your form.

Polylines.

Rectangle.

Circle.

Ellipse.

Polygone: normal or strikethrough.

Star: normal, strikethrough, flower likewise, stroked.

Text.

To know about imaging processing¶

The pixels mystery¶

An (raw) image is composed from pixels as you know.

Every pixel can be encoded on:

Basic pixel encoding¶

On a single value between 0 and 255: This is the case of gray images.

In this case every pixel can take a value from 0 (black) to 255 (white).

To create every grayscale range value.

On 3 or 4 channels of colors for every pixel.

These channels are:

The red channel which can take a value between 0 (black) and 255 (fully red).

The green channel which can take a value between 0 (black) and 255 (fully green).

The blue channel which can take a value between 0 (black) and 255 (fully blue).

And a optional fourth channel can add an opacity value: which can take a value between 0 (fully transparent) and 255 (fully opaque):

What mean that the image can contains fully transparent pixels, what permit to display a form which according per example your desktop background.

For every pixel: so the pixels are encoded on 3 or 4 values between 0 and 255 representing the red, green, blue and optionnaly alpha channel values.

What give us the RGB(A) color space.
This is not very intuitive and this is not the way humans think about colors.

But the red, green and blue values combined together give us a wide gamut of different colors
256 × 256 × 256 = 16777216 (differents possible colors).
Note

In fact, the human visual system is also based on the trichromatic perception of colors.

With cone cell sensitivity located around the red, gren and blue spectrum.

This is the common pixel encoding in digital imaging.

examples:

A fully red pixel will take following values:

Channel Red Green Blue

Value 255 0 0

Resulting color:

Note

Red is a base color because only one channel is set.

A fully green pixel will take following values:

Channel Red Green Blue

Value 0 255 0

Resulting color:

Note

Green is a base color because only one channel is set.

A fully blue pixel will take following values:

Channel Red Green Blue

Value 0 0 255

Resulting color:

Note

Blue is a base color because only one channel is set.

A fully yellow pixel will take following values: We mix red and green to obtain yellow color.

Channel Red Green Blue

Value 255 255 0

Resulting color:

Note

Yellow is a composite color because 2 differents channels are set.

A fully pink pixel will take following values: We mix red and blue to obtain pink color.

Channel Red Green Blue

Value 255 0 255

Resulting color:

Note

Pink is a composite color because 2 differents channels are set.

A fully turquoise pixel will take following values: We mix the green and blue to obtain the turquoise color.

Channel Red Green Blue

Value 0 255 255

Resulting color:

Note

Turquoise is a composite color because 2 differents channels are set.

A emboss gray pixel encoded on RGB (Red, Green, Blue) look’s like this:

Channel Red Green Blue

Value 127 127 127

Resulting color:

Note

Gray is a composite color because the 3 channels are set.

Gray can be encoded on a single value: a 1 byte encoding.

Other pixels encoding¶

Otherwise they are other image coding system’s: the phenomenal color spaces.

Which are based on the concept of

Hue.

Saturation.

And brightness.

These properties are more intuitive for humans.

The phenomenal color spaces have been introduced because they correspond to the way humans tend to naturally organized colors.

With atributes like:

Tint.

Colorfullness.

And brightness.

Hue: represent the dominant color.

The name you give to a color correspond to the hue value.

The hue value varies from 0 to 180 by representing the dominant color on a circle (0-360 degrees) which value is divide per 2 for encoding convienence.

or in others words the hue represent the tint of the color.
Saturation: represent how vivid the color is.
The saturation varies from 0 to 255 (pure spectrum color).
The saturation represent the vivid of the colors:

Low value : pastel color.

High value : rainbow color.
             max(red, green, blue) - min(red, green, blue)
Saturation = ---------------------------------------------
                       max(red, green, blue)
Brightness: represent the luminosity of a color.

This is an subjectiv attribute.

Note

Others phenomenal color spaces values use the concept of value or lightness as a way to charaterize the relativ color intensity.

Note

This colors attributes try to mimic the intuitive human pereption of colors.

Example: the HSB color space.

The hue is the cone top circle.

The brightness is the cone height.

The saturation value depends from the length of the arrow which must ne oriented into the direction of the hue value.

The Convolution kernels¶

A kernel is a set of weights which determine how each output pixel is calculated from a neighborhood of input pixels.

Applying a kernel filter consist of moving the kernel over each pixel of an image and multiplying each corresponding pixel by it’s associated weight.

According to that the central pixel correspond to a pixel of interest and the others to the neighborhood pixels.

The kernel is an odd matrix of values from any (odd) size limited from 3x3 to 31x31 and can be from different forms:

Kernels forms¶

A square type kernel matrix:

1 1 1 1 1

1 1 1 1 1

1 1 1 1 1

1 1 1 1 1

1 1 1 1 1

A diamond type kernel matrix:

0 0 1 0 0

0 1 1 1 0

1 1 1 1 1

0 1 1 1 0

0 0 1 0 0

A cross type kernel matrix:

0 0 1 0 0

0 0 1 0 0

1 1 1 1 1

0 0 1 0 0

0 0 1 0 0

An X type kernel matrix:

1 0 0 0 1

0 1 0 1 0

0 0 1 0 0

0 1 0 1 0

1 0 0 0 1

The art which the values are multiply depends from the operator which use the matrix, and the central pixel value depend from it.

The total summe of the matrix values represent the weight of the matrix and so we often adjust the value of the central pixel to make the total weight equal to:

1 or 0

but not always because it depends from how the value are interpolate:

Classical kernel matrixes¶

A sharpen kernel matrix:

-1 -1 -1

-1 9 -1

-1 -1 -1

has a weight of +1 due of the 8 x -1 values and the central +9 value.

A Find Edges kernel matrix:

-1 -1 -1

-1 8 -1

-1 -1 -1

has a weight of 0 due of the 8 x -1 values and the central +8 value.

A Emboss kernel matrix:

-2 -1 0

-1 1 1

0 1 2

has a weight of +1 due of the (-2 + -1 + 1) and (2 + 1 + 1) values and the central 1 value.

A Mean kernel matrix:

1/9 1/9 1/9

1/9 1/9 1/9

1/9 1/9 1/9

has a weight of +1 du of the fact that all values are equal to 1.0 divide per kernel size.

A Gaussian kernel matrix:

is based on a gaussian vector: a vector of values seed from a sigma value.

example from a gausssian vector from size 7 with 1.2 as sigma value:
```
[ 0.015, 0.083, 0.236, 0.333, 0.236, 0.083, 0.015 ]
```

A Kirsch kernel matrix:

Have an orientation:
- East orientation:
  
  -3 -3 5
  
  -3 0 5
  
  -3 -3 5
- West orientation:
  
  5 -3 -3
  
  5 0 -3
  
  5 -3 -3
- North orientation:
  
  -3 -3 -3
  
  -3 0 -3
  
  5 5 5
- South orientation:
  
  5 5 5
  
  -3 0 -3
  
  -3 -3 -3

A Sobel kernel matrix:
- horizontally:
  
  -1 -2 -1
  
  0 0 0
  
  1 2 1
- Vertically:
  
  -1 0 1
  
  -2 0 2
  
  -1 0 1

A Laplacian kernel matrix:

0.5 1.0 0.5

1.0 6 1.0

0.5 1.0 0.5

Thresholding¶

The use of thresholding can be used to obtain a binary image (black and white image) by setting a value: the threshold value.

In relationship to this value, all pixels values (encoded on a single value) greater as this value are set to white.

All pixels littler are set to black.

What produce a binary image map of the source image.

Note

Thresholding can be invert so that greater values are set to black and littler are set to white.

What permit to get a White and a Black version of the filters producing a binary image.

It exist algorithms which can determine the best threshold value based on the analysis of a grayscale image:

OTSU algorithm. (As in the Binary White OTSU or Binary Black OTSU filters.)

TRIANGLE algorithm. (As in the Binary White TRIANGLE or Binary Black TRIANGLE filters.)

Note

You can take the average value from this 2 algorithms computed threshold values

As in the Binary White Average or

the Binary Black Average filters.

Binary images¶

Binary images are strictly black and white images with as convention that:

The foreground from the image is represented in white.

The background from the image is represented in black.

Files¶

Supported image file formats¶

Edip support normally following images files formats to load into the program for processing:

bmp, dib (bitmap image file.)

jpg, jpeg, jpe (Join photographic Expert Group.)

png (Protable Network Graphics.)

tiff, tif (Tag(ged) Image File (Format).)

ras, sr (Sun Raster).

pbm, pgm, ppm (Portable Image Format.)

webp.

The image file is loaded into the program and converted into RGB, (internally BGR) format or RGBA (internally BGRA) if an alpha channel is available in the image.

Note

For supporting an image filetype the required library need to be installed except for:

bmp, dib (bitmap image file.)

pbm, pgm, ppm (Portable Image Format.)

ras, sr (Sun Raster).

Which are always supported.

Load images files¶

You can load an image file to process it into Edip by clicking on the Open button in the buttonbar,

through the menu item Files ‣ Open file or by hitting the shortcut Ctrl + O.

You can start the program with am image file path as argument:
$ edip image_filepath
You can open an recent image file by using the menu item Files ‣ Recent files.

Saving image files¶

You can save an image file by pressing the button Save in the button bar,

trough the menu item Files ‣ Save file or by hitting the shortcut Ctrl + S.

Then you can set the output size of the image which default to the originally image size.

And setting some options in relatinship to the format if available.

Image file format saving options¶

png image file saving options¶

Compression: from level from 0 to 9. A higher value means a smaller size and longer compression time. Default value is 3.

Strategy:

Default.

Filtered.

Huffman only.

RLE.

Fixed.

Bilevel:

You can only store an image as bilevel if the image is a binary (black and white) image.

Otherwise the result will be undefined.

jpeg image file saving options¶

Quality: it can be a quality from 0 to 100 (the higher is the better). Default value is 95.

Features:

Progressiv (disabled per default).

Optimize (disabled per default).

RST Restart: JPEG restart interval, 0 - 65535, default is 0 - no restart.

LUMA quality: Separate luma quality level, 0 - 100, default is 0 - don’t use.

CHROMA quality: Separate chroma quality level, 0 - 100, default is 0 - don’t use.

xpm image file saving options¶

Binary: For PPM, PGM, or PBM, it can be a binary format flag, 0 or 1. Default value is 1.

webp image file saving options¶

Quality: For WEBP, it can be a quality from 1 to 100 (the higher is the better). By default and for quality above 100 the lossless compression is used.

Images Files Merging¶

Edip provide severals files merging algorithms which permit to combine 2 input files to an single output file through an image mixing algorithm.

You can choose 2 differents input image files, in any supported format, with giving eventual settings, to merge it into a single ouput image file.

The differents images must have the same size to be interpolated, so Edip resize the output image to the same size, to the littler image file size from the twos per default.

But you can set the output size you want for your output image.

Then you can save the result of the image files merging to any supported format, by clicking on the Save file button.

Files merging Blend algorithm¶

Interpolate 2 images file with the constant alpha to generate an output image:
Result = Image1 * alpha - (1-alpha) * Image2
You must set the value of alpha which default to 0.5 between 0.01 and 1.0.

The images are converted to the same size (to the littler image) was is required for blend operation.

Note

You can use the button Preview result to preview your output image.

If the output size is greater than 800x600 pixels the preview image is resize to be included in the image preview window.

Files merging Screen algorithm¶

Superimpose two inverted images on the top of each other:
Result = MAX - ((MAX-Image1)  * (MAX-Images2) / MAX)
The images are converted to the same size (to the littler image) was is required for screen operation.

Note

You can use the button Preview result to preview your output image.

If the output size is greater than 800x600 pixels the preview image is resize to be included in the image preview window.

Files merging Darker algorithm¶

Interpolate 2 images file and produce an output image with the darkest pixels values:
Result = min( Image1, Image2 )
The images are converted to the same size (to the littler image) was is required for darker operation.

Note

You can use the button Preview result to preview your output image.

If the output size is greater than 800x600 pixels the preview image is resize to be included in the image preview window.

Files merging Lighter algorithm¶

Interpolate 2 images file and produce an output image with the lightest pixels values:
Result = max( Image1, Image2 )
The images are converted to the same size (to the littler image) was is required for lighter operation.

Note

You can use the button Preview result to preview your output image.

If the output size is greater than 800x600 pixels the preview image is resize to be included in the image preview window.

Files merging Add algorithm¶

Add 2 images, dividing the result by scale and adding offset to generate an output image:
Result = (Image1 + Image2) / scale + offset
You must set the value of scale which default to 1.0 between 0.01 and 8.0.

You must set the value of offset which default to 0 between 0 and 255.

The images are converted to the same size (to the littler image) was is required for add operation.

Note

You can use the button Preview result to preview your output image.

If the output size is greater than 800x600 pixels the preview image is resize to be included in the image preview window.

Files merging Add modulo algorithm¶

Add 2 images and make the euclidian division of the result per the maximal:
Result = ( Image1 + Image2 ) % MAX
The images are converted to the same size (to the littler image) was is required for add modulo operation.

Note

You can use the button Preview result to preview your output image.

If the output size is greater than 800x600 pixels the preview image is resize to be included in the image preview window.

Files merging Subtract algorithm¶

Subtract 2 images, dividing the result by scale and adding offset to generate an output image:
Result = (Image1 - Image2) / scale + offset
You must set the value of scale which default to 1.0 between 0.01 and 8.0.

You must set the value of offset which default to 0 between 0 and 255.

The images are converted to the same size (to the littler image) was is required for sub operation.

Note

You can use the button Preview result to preview your output image.

If the output size is greater than 800x600 pixels the preview image is resize to be included in the image preview window.

Files merging Subtract modulo algorithm¶

Subtract 2 images and make the euclidian division of the result per the maximal:
Result = ( Image1 - Image2 ) % MAX
The images are converted to the same size (to the littler image) was is required for sub modulo operation.

Note

You can use the button Preview result to preview your output image.

If the output size is greater than 800x600 pixels the preview image is resize to be included in the image preview window.

Simple Settings¶

You will find the simple settings on the right sidebar from Edip.

You can switch between Intensity and Colorspace with the corresponding buttons.

Intensity¶

Here you can change the color intensities with the corresponding scales.

Red: from -255 to 255.

Set the wanted red intensity change and press the Apply button.

If the selected value is greater than 0 it will add the selected value to the red channel from all pixels of your image.

If the selected value is littler than 0 it will subtract the selected value from the red channel from all pixels of your image.

Green: from -255 to 255.

Set the wanted green intensity change and press the Apply button.

If the selected value is greater than 0 it will add the selected value to the green channel from all pixels of your image.

If the selected value is littler than 0 it will subtract the selected value from the green channel from all pixels of your image.

Blue: from -255 to 255.

Set the wanted blue intensity change and press the Apply button.

If the selected value is greater than 0 it will add the selected value to the blue channel from all pixels of your image.

If the selected value is littler than 0 it will subtract the selected value from the blue channel from all pixels of your image.

Global: from -255 to 255.

Set the wanted intensity change and press the Apply button.

If the selected value is greater than 0 it will add the selected value to the all channels from all pixels of your image.

If the selected value is littler than 0 it will subtract the selected value from the all channels from all pixels of your image.

Colorspace¶

Here you can set:

The Lightness from your image.

The Hue from your image.

The Saturation from your image.

The Brightness from your image.

Simple Filters¶

Edip built-in filters¶

Edip provide a lot of predefine, non-configurable built-in filters, applicable like this:

Pencil Sketch¶

The Pencil Sketch filter produce a non-photorealistic line drawing image.

Stylisation¶

The stylisation filter is an edge-aware filters which effect is not focused on photorealism but abstract regions of low contrast while preserving, or enhancing, high-contrast features.

Detail Enhance¶

The Detail Enhance filter enhances the details of a particular image.

Edges Preserving¶

The Edge Preserving filter is a smoothing filters used in many different applications.

Stroke Edges¶

The Stroke Edges filter add black strokes on some edges of the image.

Invert Intensity¶

The Invert Intensity filter invert the intensity.

This mean that the maximal value become the minimal value and so soon in the pixel values range.

Light Intensity¶

The Light Intensity filter invert the intensity from the pixels channels average value.

So that it output an grayscale image with light effect.

Recolor RC (Red-Cyan)¶

Simulate conversion from RGB (Red, Green, Blue) to RC (red, cyan).

Blues and greens are replaced with cyans.

The effect is similar to Technicolor Process 2 (used in early color movies) and CGA Palette 3 (used in early color PCs).

Recolor RGV (Red-Green-Value)¶

Simulate conversion from RGB (Red, Green, Blue) to RGV (red, green, value).

Blues are desaturated.

The effect is similar to Technicolor Process 1 (used in early color movies).

Recolor CMV (Cyan-Magenta-Value)¶

Simulate conversion from RGB (Red, Green, Blue) to CMV (cyan, magenta, value).

Yellows are desaturated.

The effect is similar to CGA Palette 1 (used in early color PCs).

Extrema Maximal¶

The Extrema Maximal filter compute the maximal values from 2 differents channels and set the result on a channel.

Extrema Minimal¶

The Extrema Minimal filter compute the minimal values from 2 differents channels and set the result on a channel.

Sharpen¶

The Sharpen filter sharpen the image by adding some white pixels at some edges and points of the image.

This filter is based on a Sharpen convolution matrix.

Sharpen More¶

The Sharpen More filter sharpen the image by adding some white pixels at some edges and points of the image.

It has more impact on the image as the Sharpen filter but does the same stronger.

This filter is based on a Sharpen convolution matrix.

Find Edges¶

The Find Edges filter will result in black background image with the contours and some pixels, of the source image, displayed in color.

This filter is based on a Find Edges convolution matrix.

Mean Blur¶

The Mean Blur filter swindle the image. The result image is blurred.

This filter is based on a Mean convolution matrix.

Mean Blur More¶

The Mean Blur More filter swindle the image. The result image is blurred.

It has more impact on the image as the Mean Blur filter but does the same stronger.

This filter is based on a Mean convolution matrix.

Blur¶

The Blur filter swindle the image.

What can remove some noise of the image or smooth an pixelize image.

Blur Median¶

The Blur Median filter swindle the image.

What can remove some noise of the image or smooth an pixelize image.

This filter is well know for salt and pepper noise removing.

Blur Gaussian¶

The Blur Gaussian filter swindle the image.

What can remove some noise of the image or smooth an pixelize image.

It use gaussian values for creating the blurring effect applying onto the image.

Denoising¶

The denoising filter perform image denoising using Non-local Means Denoising with several computational optimizations.

Noise expected to be a gaussian white noise.

Denoising is done by converting image to CIELAB colorspacenand then separately denoise L and AB components with different parameters.

Erode¶

The Erode filter eroding the image content contours.

This filter erodes the image by minimizing the pixels neighborhood.

Dilate¶

The Dilate filter dilate the image content contours.

This filter dilates the image by maximizing the pixels neighborhood.

Wave Horizontally¶

The Wave Horizontally filter output an horizontally waved image.

Wave Vertically¶

The Wave Vertically filter output an horizontally waved image.

Wave Twice¶

The Wave Twice filter output an horizontally and vertically waved image.

Contours Sobel White¶

The Contours Sobel White filter result in an image with a white background and colored drawning wise foreground.

All the contours strokes of the image will be displayed on a white background.

Contours Sobel Black¶

The Contours Sobel Black filter result in an image with a black background and colored drawning wise foreground.

All the contours strokes of the image will be displayed on a black background.

Contours Sobel Emboss¶

The Contours Sobel Emboss filter result in an image with an emboss gray background and colored drawning wise foreground.

All the contours strokes of the image will be displayed on a emboss gray background.

Emboss Sobel¶

The Emboss Sobel filter is an emboss filter which result looking like a kopper engraving.

Based on the Sobel operator which detect edges horizontally and or vertically.

Emboss Laplacian¶

The Emboss Laplacian filter is an emboss filter which result looking like a kopper engraving.

Based on the Laplacian operator which detect edges horizontally and vertically.

Binary White OTSU¶

The Binary White OTSU filter create an black and white image, from the source image, with white background and black foreground.

Based on the OTSU image specific threshold computing algorithm.

Simply try every algorithm to find the appositely one for your image, to get the best binary image from it.

Binary White TRIANGLE¶

The Binary White TRIANGLE filter create an black and white image, from the source image, with white background and black foreground.

Based on the TRIANGLE image specific threshold computing algorithm.

Simply try every algorithm to find the appositely one for your image, to get the best binary image from it.

Binary White AVERAGE¶

The Binary White AVERAGE filter create an black and white image, from the source image, with white background and black foreground.

Based on the OTSU and TRIANGLE image specific threshold computing algorithm, average.

Simply try every algorithm to find the appositely one for your image, to get the best binary image from it.

Binary Black OTSU¶

The Binary Black OTSU filter create an black and white image, from the source image, with black background and white foreground.

Based on the OTSU image specific threshold computing algorithm.

Simply try every algorithm to find the appositely one for your image, to get the best binary image from it.

Binary Black TRIANGLE¶

The Binary Black TRIANGLE filter create an black and white image, from the source image, with black background and white foreground.

Based on the TRIANGLE image specific threshold computing algorithm.

Simply try every algorithm to find the appositely one for your image, to get the best binary image from it.

Binary Black AVERAGE¶

The Binary Black AVERAGE filter create an black and white image, from the source image, with black background and white foreground.

Based on the OTSU and TRIANGLE image specific threshold computing algorithm, average.

Simply try every algorithm to find the appositely one for your image,nto get the best binary image from it.

Binary Contours White¶

The Binary Contours White filter create an black and white image, from the source image, with white background and black foreground.

With as foreground all the contours strokes of the image.

Like an black and white drawning.

Binary Contours Black¶

The Binary Contours Black filter create an black and white image, from the source image, with black background and white foreground.

With as foreground all the contours strokes of the image.

Like an black and white drawning.

Simple Grayscaling¶

Edip can grayscaling your image, to set it enterely in gray tone, according differents bases:

Gray Scaling Average.
Gray Scaling Maximal.
Gray Scaling Minimal
Gray Scaling Red.
Gray Scaling Green.
Gray Scaling Blue.

Edip will process all the pixels of your images to compute the wanted gray values.

To know that either a gray pixel can be encoded on a single value between 0 and 255 or

setting all channels on the same value will result in a gray pixel too.

For example let say the current pixel Edip is procesing has the following channels values:

Channel Red Green Blue

Value 32 128 192

Gray Scaling Average:
Edip will compute the average from all channels and set the result as gray value.

So Edip compute the average value:
(32 + 128 + 192) / 3 = 117.
So the resulting pixel will be transform to have following values:

Channel Red Green Blue

Value 117 117 117

Or be encoded on a single value equal to 117.
Gray Scaling Maximal:
Edip will take the highest value from all the channels and set the it as gray value.

So Edip compute the maximal value from the channels:
32 < 128 < 192 = 192.
So the resulting pixel will be transform to have following values:

Channel Red Green Blue

Value 192 192 192

Or be encoded on a single value equal to 192.
Gray Scaling Minimal:
Edip will take the lowest value from all the channels and set the it as gray value.

So Edip compute the minimal value from the all channels:
192 > 128 > 32 = 32.
So the resulting pixel will be transform to have following values:

Channel Red Green Blue

Value 32 32 32

Or be encoded on a single value equal to 32.
Gray Scaling Red:
Edip will take the value from the red channel and set the it as gray value.

So Edip recover the red channel value which is equal to 32:
Red = 32.
So the resulting pixel will be transform to have following values:

Channel Red Green Blue

Value 32 32 32

Or be encoded on a single value equal to 32.
Gray Scaling Green:
Edip will take the value from the green channel and set the it as gray value.

So Edip recover the green channel value which is equal to 32:
Green = 128.
So the resulting pixel will be transform to have following values:

Channel Red Green Blue

Value 128 128 128

Or be encoded on a single value equal to 128.
Gray Scaling Blue:
Edip will take the value from the green channel and set the it as gray value.

So Edip recover the blue channel value which is equal to 192:
Blue = 192.
So the resulting pixel will be transform to have following values:

Channel Red Green Blue

Value 192 192 192

Or be encoded on a single value equal to 192.

Note

Edip will compute every pixel from your image like explain above according the choosen grayscaling base.

Simple Colorscaling¶

Edip can colorscaling your image, to set it enterely in a main color tone, according differents bases:

In red tone:
- Red Scaling Average.
- Red Scaling Maximal.
- Red Scaling Minimal.
- Red Scaling Green.
- Red Scaling Blue.
In green tone:
- Green Scaling Average.
- Green Scaling Maximal.
- Green Scaling Minimal.
- Green Scaling Red.
- Green Scaling Blue.
In blue tone:
- Blue Scaling Average.
- Blue Scaling Maximal.
- Blue Scaling Minimal.
- Blue Scaling Green.
- Blue Scaling Blue.
In yellow tone:
- Yellow Scaling Average.
- Yellow Scaling Maximal.
- Yellow Scaling Minimal.
- Yellow Scaling Red.
- Yellow Scaling Green.
- Yellow Scaling Blue.
In pink tone:
- Pink Scaling Average.
- Pink Scaling Maximal.
- Pink Scaling Minimal.
- Pink Scaling Red.
- Pink Scaling Green.
- Pink Scaling Blue.
In turquoise tone:
- Turquoise Scaling Average.
- Turquoise Scaling Maximal.
- Turquoise Scaling Minimal.
- Turquoise Scaling Red.
- Turquoise Scaling Green.
- Turquoise Scaling Blue.

Note

The pixels values computing according the differents bases are the same at by grayscaling.

Advanced Configurable Filters¶

Kernel filters¶