Re: How to read 'raw' data as 32 bit unsigned in Java

Posted by Robert Lockwood on Feb 12, 2019; 10:21pm
URL: http://imagej.273.s1.nabble.com/How-to-read-raw-data-as-32-bit-unsigned-in-Java-tp5021772p5021780.html

Thanks, Kenneth, this is a stand-alone program to detect adjacent pixels
that have the same values and save the probably converted data as grayscale
with the detected pixels in color.

Here is the code I have now, compiles and runs but unfinished

            // read raw image file
            byte[] bytes = Files.toByteArray(dFile);
            // represent as integers
            IntBuffer rawIntImage = ByteBuffer.wrap(bytes).asIntBuffer();

            // set up for data using imageJ
            final ImagePlus imp = IJ.createImage(dFile.getName(), "16-bit",
                    NCOLS, NROWS, 1);
            final ShortProcessor sp = (ShortProcessor) imp.getProcessor();
            final short[] shortImage = (short[]) sp.getPixels();
            int index = 0;
            while(rawIntImage.hasRemaining()) {
                shortImage[index++] = (short) rawIntImage.get();
            }
            // sp.convertToByte(true).convertToRGB(); // What is returned
here?

I need "IntBuffer rawIntImage" to use to detect the adjacent duplicate
pixels
I'm assuming that 'convertToByte' will do the brightness and contrast
mapping returning a ByteProcessor, is that correct?  Then I need to convert
to RGB ?


On Tue, Feb 12, 2019 at 1:19 PM Kenneth Sloan <[hidden email]>
wrote:

> Ah...if the data are really 16-bit, then my recommendation is to
> import the image as a 32-bit float, apply Brightness/Contrast,
> and use an OVERLAY to highlight the problem pixels.
>
> But, if you really want RGB, import as 32-bit, adjust,
> and use Image->Type->RGB and you are done.
>
> Note that this loses precision (but, you can't see much more than
> 8-bits on the screen anyway).
>
> You also lose access to the actual original pixel values - but
> perhaps that's not important.
>
> I do this routinely with data that claim to be 32-bit floats in the
> range [0.0..1.0).  These are essentially 24-bit unsigned integers.
>
> It looks like there is no reason for you to import a byte array
> and twiddle bits to construct ints.  Fiji will happily import
> the image as 32-bit float, adjust brightness/contrast, and convert
> to RGB (if that's what you want).
>
> Is your code to find and highlight problem pixels written as a
> Fiji plugin, or as a stand-alone Java program?
>
>
> --
> Kenneth Sloan
> [hidden email]
> Vision is the art of seeing what is invisible to others.
>
>
>
>
>
> > On Feb 12, 2019, at 14:48, Robert Lockwood <[hidden email]> wrote:
> >
> > When I look at the imported images in Fiji I apply Brightness/Contrast
> with
> > auto for a decent image.
> >
> > If I can do the same thing in Java and then convert to RGB I can then
> > manipulate the pixels I've identified by my comparison code.
> >
> > BTW the values in my 32 bit first came from the camera as defined as C
> > unsigned shorts so all the values are less than 64K so I can extract the
> > Java short values easily.
> >
> > On Tue, Feb 12, 2019 at 11:20 AM Kenneth Sloan <[hidden email]>
> > wrote:
> >
> >> If you do this in Java, I think there are a couple of workarounds.
> >>
> >> Here's one idea: Since you already can "process these data as ints", you
> >> should be able to create your own 8-bit RGB image.  Of course, you only
> >> get 8-bits of gray scale.
> >>
> >> Here's another idea: you should be able to import the image as a 32-bit
> >> float image.  If there is non-zero data in the upper 8 bits, the image
> >> will look
> >> very strange, but at least you'll have a 32-bit array.  Next, take each
> >> 32-bit float pixel value and use Float.floatToRawIntBits to get
> >> your 32-bit integer values.
> >>
> >> Since you can already create the int values from your byte array, I
> would
> >> start
> >> with that idea.
> >>
> >> Be careful about signed/unsigned.
> >>
> >> Finally, I would consider creating a 24-bit integer gray-scale value,
> and
> >> using
> >> that as a 32-bit float (using Float.intBitsToFloat).  This gives you a
> >> float image
> >> where the values are between 0.0 and 1.0.  You can then use an Overlay
> to
> >> highlight
> >> the problem pixels.  Use either idea above to get a 32-bit unsigned
> value,
> >> and
> >> scale it to 24-bits.  Convert that to a float, and store it in a 32-bit
> >> float image.
> >>
> >> Or, simply create a 16-bit integer gray scale image, and use an Overlay.
> >>
> >> Your choice may depend on what you know about the range of values.  The
> >> advantage of
> >> my 24-bit version above is that you have a bit more flexibility in
> >> dynamically adjusting
> >> the range of displayed gray levels.  The disadvantage is that the
> numbers
> >> will all
> >> be presented as (0.0..1.0) instead of [0..65535] (for the 16-bit
> version)
> >>
> >> --
> >> Kenneth Sloan
> >> [hidden email]
> >> Vision is the art of seeing what is invisible to others.
> >>
> >>
> >>
> >>
> >>
> >>> On Feb 12, 2019, at 12:37, Herbie <[hidden email]> wrote:
> >>>
> >>> Good day,
> >>>
> >>> ImageJ doesn't support 32 bit integer gray scale images.
> >>>
> >>> Supported are 8bit and 16bit integer as well as 32bit float.
> Furthermore
> >> 24bit (3 X 8bit) RGB and index color 8bit.
> >>>
> >>> Regards
> >>>
> >>> Herbie
> >>>
> >>> :::::::::::::::::::::::::::::::::::::::::::::
> >>> Am 12.02.19 um 19:15 schrieb Robert Lockwood:
> >>>> Working with Java I have raw data files with 32 bit integer gray scale
> >> data
> >>>> which I read into a byte[] array.  I process these data as ints
> looking
> >> for
> >>>> adjacent pixels that have the same value in order to debug a problem
> >> with
> >>>> the camera.
> >>>> I'd like to create a scaled grayscale RGB from the original data so
> >> that I
> >>>> may color the detected adjacent pixels to allow us to detect patterns
> >>>> visually but I don't understand how to create and populate a grayscale
> >>>> integer ImageJ array and have not found an example by Google
> searching.
> >>>> How do I do this?
> >>>> TIA
> >>>> --
> >>>> ImageJ mailing list: http://imagej.nih.gov/ij/list.html
> >>>
> >>> --
> >>> ImageJ mailing list: http://imagej.nih.gov/ij/list.html
> >>
> >> --
> >> ImageJ mailing list: http://imagej.nih.gov/ij/list.html
> >>
> >
> > --
> > ImageJ mailing list: http://imagej.nih.gov/ij/list.html
>
> --
> ImageJ mailing list: http://imagej.nih.gov/ij/list.html
>

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