Parte I. Introducción a ImageJ Parte II – Operaciones sobre píxeles Parte III - Filtros
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
Parte I. Introducción a ImageJ Parte II – Operaciones sobre píxeles Parte III - Filtros
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.
Part II – Operaciones sobre pixeles The histogram Brightness Contrast RGB color
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
Part II – Operaciones sobre pixeles The histogram Brightness Contrast RGB color
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
Part II – Operaciones sobre pixeles The histogram Brightness Contrast RGB color
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.
Parte I. Introducción a ImageJ Parte II – Operaciones sobre píxeles Parte III - Filtros
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