parte i. introducción a imagej operaciones sobre...

Parte I. Introducción a ImageJ Parte II – Operaciones sobre píxeles Parte III - Filtros

http://rsb.info.nih.gov/ij

Resources ImageJ Web Site http://rsb.info.nih.gov/ij Tutorial http://rsb.info.nih.gov/ij/docs/guide/index.html



Of these, we’ll concentrate on:

˃ Image

˃ Process

˃ Analyze

˃ Plugins

˃ Help

Image Menu

Process Menu

Analyze Menu

Plugins Menu

Help Menu

Part II – Operaciones sobre píxeles The histogram Brightness Contrast RGB color

Part II – Operaciones sobre pixeles The histogram Brightness Contrast RGB color

The Image Histogram

Log Scale

The histogram shows the number of pixels of each value, regardless of location. The log display allows for the visualization of minor components.

In this case, the log display indicates that virtually all pixel values are used, even though they are a small percentage of the total.

Brightness/contrast

Brightness Adjustment

The brightness adjustment essentially adds or subtracts a constant to every pixel, causing a shift in the histogram along the x axis, but no change in the distribution

Contrast Enhancement

For contrast enhancement, a lower value, in this case, 88, is set at zero, and a higher value, 166, is set at 255. The values of each of the pixels are adjusted proportionately. Note that because of the integer values, not all of the pixel values are used.

Contrast Enhancement

Saturated pixels determines the number of pixels in the image that are allowed to become

saturated. Increasing this value increases contrast.

Normalize and ImageJ will recalculate the pixel values of the image so the range is equal to

the maximum range for the data type

A way to treat color is to assign a set of 3 values, for Red, Green and Blue to each pixel. For common color images, each of the three colors

is represented as an 8-bit value.

One can think of a color image as consisting of three planes, one for each of the primary colors

As we move the cursor over different parts of the image, the color values appear in the status bar of the program.

A color histogram is available, In the Analyze>Histogram>RGB

Conversion to grey scale

Since many operations will work only on grey scale images, it is necessary to consider how the conversions from color images can be accomplished.

There are two approaches, dependent on the type of image.

The simplest is to select the image, go to Image>type, and select 8-bit, or 16 or 32 bit.

However, some images, such as fluorescence micrographs taken as RGB images, can yield surprises.

The reason that the image is so dark is that the routine averages the three channels (rgb) to generate the image. Since there is no data in g or b, the values for the red channel are divided by 3, yielding a dark image.

We can overcome this by separating the three channels and discarding those with no data.

Color Merge Many fluorescence images are taken in single channel images which are often

merged to generate a single overlapped image.

Some cameras generate rgb images even of single color fluorescence In that case, the images have to be converted to 8-bit before processing.

Tutorial correspondiente a filtros en ImageJ:

http://rsb.info.nih.gov/ij/docs/guide/146-29.html#toc-Subsection-29.11

Suavizado Filtro Gaussiano

Suavizado Filtro Media

Suavizado Filtro Mediana (apropiado para ruido del tipo sal y pimienta)

Filtros mínimo y máximo

Filtros personalizados

Recursos usados para la elaboración de estas diapositivas:

» ImageJ, A Useful Tool for Image Processing and Analysis Joel B. Sheffield, Temple University.

http://rsbweb.nih.gov/ij/docs/examples/IJ-M&M08.ppt

» MRI ImageJ Workshop. Exercises 4 with solutions

http://dev.mri.cnrs.fr/wiki/imagej-workshop










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