I have one question about High Dynamic Range (HDR) images. I want to creat a high dynamic range image from exposure bracketing of grayscale images using matlab. Matlab only support creating HDR image from RBG images. I did google search but there is not many results that related to my topic. Can you advise me some papers or algorithms that could hepl me out.
thanks for any help in advance.
What about replacing grayscale image to RGB image? I haven't used HDR modules, but it maybe works.
rgbImg = zeros(size(grayImg,1), size(grayImg,2), 3);
rgbImg(:,:,1)=grayImg;
rgbImg(:,:,2)=grayImg;
rgbImg(:,:,3)=grayImg;
The HDR Toolbox for MATLAB supports building greyscale images, please have a look at:
https://github.com/banterle/HDR_Toolbox
or
http://www.advancedhdrbook.com
It also supports SIFT and WARD alignment, if you have not use a tripod for capturing images.
Related
I have a small problem with finding the pixel size of an image. I am to find size of nano and micro particles on my BW image. I used regionprops to get the area - then the diameter. Now i know the value in pixels. How do i convert to micro or nano meter scale? Do I take into account the sensor size(6.5umx6.5um) of my camera?
I use MATLAB for image processing.
Thank you
there is a function called imfinfo which will return a struct. In this struct you will maybe find three fields (it depends on the coder that you used for the image format) called XResolution, YResolution and ResolutionUnit. Using this 3 fields you can easily get pixel size, for example if XResolution=10, YResolution=10 and ResolutionUnit='meter' then you have a 100cm2 pixels (its a bit unreal i know :))
I hope this helps and that your image file contains the XResolution and YResolution information in your header.
I have a matlab code and it generates a .png image of 1024*768 resolution. The images are about 450KB in size and I need to know how to optimise and compress these images using matlab.
Can't I play with the quality as in JPEG ?
I read the imwrite manual and don`t seem to find a good way to do this.
Is there any way to achieve it in matlab ?
By design PNG files are lossless - there is no 'quality' to be adjusted (it's probably why a mod changed your question title).
You can reduce the number of colors in the image (the color depth) which will in turn reduce filesize (PNG-8 instead of PNG-24, for example), but the whole point of PNG is it produces lossless images, so there is simple no quality value a la JPEG.
Taken from the manual :
A parameter of input in case it is JPEG:
'Quality' - A number between 0 and 100; higher numbers mean higher quality (less image degradation due to compression), but the resulting file size is larger.
imwrite(x,'c:\1.jpg','Quality',10)
edit: Sorry, I answered this one while the title was JPEG and not PNG.
PNG doesn't support any quality settings - it is a lossless format. The compression it applies is generally as good as possible.
JPEGs are smaller in size than PNGs. So, I thought that if I can make a specific region in a JPEG-file transparent, with some code, maybe I can save some bytes.
So does anyone know how to achieve this with for example PHP or JavaScript?
No. You can't do this. JPGs do not support alpha channels and have no capacity to designate certain colors as transparent either (GIF-style).
There's several issues with this, all of them have to do with that JPEG is a lossy compression format. The JPEG format is optimized for natural images and sharp edges will get blurred. If you intend that a specific pixel should have the value #d67fff there's no guarantee that after color conversion, FDCT, quantization, IDCT and color conversion, the pixel still will have that value. There's also a strong possibility that that pixel value will occur in areas that you don't want.
No. JPEG does not support transparency and is not likely to do so any time
soon. http://www.faqs.org/faqs/jpeg-faq/part1/section-12.html
You cannot do that, the client renders the image and doesn't know that you want it to treat that color as transparent (plus various compression methods on jpeg wouldn't work well with transparencies anyway).
I believe you can go with an 8-bit custom-pallet png, should save you a lot of space. Otherwise 24-bit PNG is your only high color option.
You can convert your image to SVG containing a color information as JPEG and an alpha channel as grayscale mask. Here is a tool I wrote to do it https://github.com/igrmk/transpeg
I am trying to implement a histogram equalization method (HE) for a UIImage in my iphone app.
I read the following:
http://en.wikipedia.org/wiki/Histogram_equalization
But it says:
Still, it should be noted that applying the same method on the Red, Green, and Blue components of an RGB image may yield dramatic changes in the image's color balance since the relative distributions of the color channels change as a result of applying the algorithm. However, if the image is first converted to another color space, Lab color space, or HSL/HSV color space in particular, then the algorithm can be applied to the luminance or value channel without resulting in changes to the hue and saturation of the image.
So would this be a feasible approach?
Grab UIImage data and convert from RGB to HSL
Apply HE on luminance channel
convert data back to RGB
Create new UIImage from data
Will this be slow, I wonder? Also, will I have to deal with 8/16/24 bit data differently, as I have no idea what kind of image will be used with my app? Or can I assume 24 bit for images in the iPhone?
I would appreciate any pointers to objective-C code that does color corrected histogram equalization.
I have looked at the library below, but it does not do any color correction for HE:
http://code.google.com/p/simple-iphone-image-processing/source/browse/#svn/trunk/Classes%3Fstate%3Dclosed
Thanks!
Yes you can do it this way, that will work. Yes it will "cost more" since you have to do the conversion back and forth - but that's the price you will have to pay if you don't want to affect the hue and saturation. Is that worth it for the images you're correcting? It would depend on your application, are you OK with a hit in performance vs best quality? You will likely only have to deal with 8bit color components, you can assume "24 bit" for images but that's 3 x 8bit components The only way to know your answers though is to try.
I recommend using YUV Colorspace. Both for accuracy and for computation simplicity (Linear Combination).
One method would be applying the histogram equalization on the RGB image (Image2).
Then let the user to chose what he wants, Apply only on luminosity or all 3 channels.
For the first choice take UV channels of the original image with the Y channel of the equalized image and convert back to RGB.
For the second choice just leave the user with Image2.
Since after transformation, you deal with I/V as being continuous values, you will have to apply some binning strategy, which results in a step Histogram for the quantity you wish to equalize. Therefore, you might speed this up by reducing the bin size?
Just write the codes and model applying HE to each of the RGB component. Although there are much calculation for its 3 components, but programming speed is OK. In most of the cases, the contrast is improved, but the "look" of the image is changed. So agree to transform the RGB into another space then apply the HE again. I am looking for the formula and also the correct color space for the HE. Which color space is easier?
I write the HE in the iPad platform, but I find after opening a big image taken from my Canon, the whole program crashes after UIPopoverContoller, UIImagePickerController functions. I think it maybe due to I am pushing too much on the phone's OS, or the OS allocates only a limit amount of memory space for each of the apps. If apps is using more than pre-set memory, then the iOS just kills the apps right away. So must take care of the size of the input image, and the garbage collection of unused memory, and memory leak. Using XCode's instrument tool to check for leakage is a must.
I want to take an image of blurry cylindrical objects and get rid of the blur, basically sharpen the image. How do I do that in Matlab?
See the "sharpening" section in http://www.aquaphoenix.com/lecture/matlab10/page3.html.
You can do it with filters.
See here, section 10.2.4 here: http://www.aquaphoenix.com/lecture/matlab10/page3.html
In addition to all the good answers by others: for the very very simple inputs, you can simply threshold the image if you just need the boundary of those cylinders.