What about sharpen a picture? I didn't find a way to sharpen a picture after resizing it. When I resize a large picture, it seems to be a bit blurry. At least my customers want to have a more "crispy" look.
With the AdvancedFilters plugin installed, you can apply an unsharp mask with &a.sharpen=radius.
By default a Bicubic Smoother resampling filter is applied, as this gives the best results for nearly all photographs.
Related
I am a beginner at graphics and I was wondering if anyone had any experience in programmatically splitting isometric tile sheets, in particular Reiner Tile Sheets Here is an Example Image:
.
I have been splitting it using guides by hand in gimp but there is some sort of pattern going on that I feel can be used to programmatically split this. Before I tried to make my own, I wanted to see if there was any such algorithms premade / software that could do it currently. Its not a simple grid that needs to be cut with same width and height for each one. Thanks for the help!
Some stuff for thinking and read
First take a look at:
2D Diamond (isometric) map editor - Textures extended infinitely?
for some inspiration. Especially take a look at (3. tile editor) part. The operations described there are exactly what you are looking for (to add the missing stuff you are doing manually right now).
However your tile set is oriented differently so the masks will be slightly different ...
In case you want to extract tileset from image you would need something like this:
Grid image values to 2D array
And also take a look at this (for even more inspiration):
Improving performance of click detection on a staggered column isometric grid
The pixel perfect O(1) mouse selection at the end is a good idea to implement.
Your tile map
so you have a tilemap image but you do not have the tiles boundaries. So first identify tileset resolution... There might be more tile sizes present so you need to know all of them. Your image is 256x1024 pixels and from a quick look you have 32x32 pixels tiles. Most of the tiles are 64x64 however they are constructed from 4 tiles of 32x32 pixels. The white color is the transparent one. So you just divide the image to 32x32 squares or regroup to 64x64 ones.
I want to make publication-quality plots with Matplotlib. The biggest problem I am having right now is to tune the image and font sizes.
When I create a figure with several panels, I usually set a bigger figsize. For example, these three panels are created with a figsize=(12, 6 / 1.618) (pasted from Jupyter Lab, I always save to PDF files).
The lines can be perfectly seen, there is a lot of space, the figure seems nice. The problem is that in my publication this has to be a column-wise figure, so it has to be scaled down. A colum has a width of around ~3.5 inches. When the image is resized, it still looks good, but the axes labels become very tiny and unreadable. Of course, I can just simply start increasing the font sizes until I find a good size, but I would like to have a workflow that allows me to work with the lengths and sizes I have to use.
When I set the image size to figsize=(columnw, 0.5*columnw / 1.618) (so the aspect ratio is the same) as before, and set the font size around 10 (the font size of my publication) this is what I get:
So now the fonts are exactly the size I want them to be, the figure does not have to be reescaled, but the contents of the graph seem to be compressed into a very very tiny space. It just look... ugly.
Then, my question is: why using a big figsize with extremely large fontsizes gives a beautiful, readable figure when scaled, but with the a priori correct figsize without rescaling seems to be ugly? How could I work with real figsizes from the very beginning to obtain something nice?
I read some questions regarding image size with Matplotlib on this site, as well as a pair of blog posts, but I haven't found any information regarding this problem.
Thank you in advance.
<------This is an image I made in Photoshop...
It's basically a 160 x 160 box of white with a texture applied.
Below is what it looks like with "background-repeat" in the CSS. I was hoping it'd balance out. Is there a certain percentage the textile has to be at, or size of the original box? For it to be a perfect repeatable texture?
Im trying to do this myself, since I cant find grid patterns that fit the style.
Question: Whats the trick on making textures in Photoshop, that appear as balanced whole backgrounds when repeated?
If you look at the below image where it's in effect, on the very basic start of what Im working on, you can notice it doesnt quite fit together.
Any and all help greatly appreciated. Thanks in advance.
If you want that background for a webpage is better the use of repeating-linear-gradient. It is very easy of implement, less assets to download and it is supported by major browsers.
Look in the top left corner of your image. You'll note that the dark line starts at roughly 4-5 pixels from the top. Then look at the top right corner, and you'll note that the top line starts at just perhaps 2px from the top.
When this image is repeated twice side by side, there will be a disconnect. Just crop the image and shave off the two or three pixels until your lines connect. Repeat by cropping the bottom of the image for vertical alignment.
If you want to do this experimentally, increase the size of your canvas, and copy the pattern into a new 160x160 layer. Place them side by side, and then move the layers one pixel at a time so that they overlap. Where the overlap aligns is where you should crop the image.
i am trying to read an image with ITK and display with VTK.
But there is a problem that has been haunting me for quite some time.
I read the images using the classes itkGDCMImageIO and itkImageSeriesReader.
After reading, i can do two different things:
1.
I can convert the ITK image to vtkImageData using itkImageToVTKImageFilter and the use vtkImageReslicer to get all three axes. Then, i use the classes vtkImageMapper, vtkActor2D, vtkRenderer and QVTKWidget to display the image.
In this case, when i display the images, there are several problems with colors. Some of them are shown very bright, others are so dark you can barely see them.
2.
The second scenario is the registration pipeline. Here, i read the image as before, then use the classes shown in the ITK Software Guide chapter about registration. Then i resample the image and use the itkImageSeriesWriter.
And that's when the problem appears. After writing the image to a file, i compare this new image with the image i used as input in the XMedcon software. If the image i wrote ahs been shown too bright in my software, there no changes when i compare both of them in XMedcon. Otherwise, if the image was too dark in my software, it appears all messed up in XMedcon.
I noticed, when comparing both images (the original and the new one) that, in both cases, there are changes in modality, pixel dimensions and glmax.
I suppose the problem is with the glmax, as the major changes occur with the darker images.
I really don't know what to do. Does this have something to do with color level/window? The most strange thing is that all the images are very similar, with identical tags and only some of them display errors when shown/written.
I'm not familiar with the particulars of VTK/ITK specifically, but it sounds to me like the problem is more general than that. Medical images have a high dynamic range and often the images will appear very dark or very bright if the window isn't set to some appropriate range. The DICOM tags Window Center (0028, 1050) and Window Width (0028, 1051) will include some default window settings that were selected by the modality. Usually these values are reasonable, but not always. See part 3 of the DICOM standard (11_03pu.pdf is the filename) section C.11.2.1.2 for details on how raw image pixels are scaled for display. The general idea is that you'll need to apply a linear scaling to the images to get appropriate pixel values for display.
What pixel types do you use? In most cases, it's simpler to use a floating point type while using ITK, but raw medical images are often in short, so that could be your problem.
You should also write the image to the disk after each step (in MHD format, for example), and inspect it with a viewer that's known to work properly, such as vv (http://www.creatis.insa-lyon.fr/rio/vv). You could also post them here as well as your code for further review.
Good luck!
For what you describe as your first issue:
I can convert the ITK image to vtkImageData using itkImageToVTKImageFilter and the use vtkImageReslicer to get all three axes. Then, i use the classes vtkImageMapper, vtkActor2D, vtkRenderer and QVTKWidget to display the image.
In this case, when i display the images, there are several problems with colors. Some of them are shown very bright, others are so dark you can barely see them.
I suggest the following: Check your window/level in VTK, they probably aren't adequate to your images. If they are abdominal tomographies window = 350 level 50 should be a nice color level.
I'm looking for ways to determine the quality of a photography (jpg). The first thing that came into my mind was to compare the file-size to the amount of pixel stored within. Are there any other ways, for example to check the amount of noise in a jpg? Does anyone have a good reading link on this topic or any experience? By the way, the project I'm working on is written in C# (.net 3.5) and I use the Aurigma Graphics Mill for image processing.
Thanks in advance!
I'm not entirely clear what you mean by "quality", if you mean the quality setting in the JPG compression algorithm then you may be able to extract it from the EXIF tags of the image (relies on the capture device putting them in and no-one else overwriting them) for your library see here:
http://www.aurigma.com/Support/DocViewer/30/JPEGFileFormat.htm.aspx
If you mean any other sort of "quality" then you need to come up with a better definition of quality. For example, over-exposure may be a problem in which case hunting for saturated pixels would help determine that specific sort of quality. Or more generally you could look at statistics (mean, standard deviation) of the image histogram in the 3 colour channels. The image may be out of focus, in which case you could look for a cutoff in the spatial frequencies of the image Fourier transform. If you're worried about speckle noise then you could try applying a median filter to the image and comparing back to the original image (more speckle noise would give a larger change) - I'm guessing a bit here.
If by "quality" you mean aesthetic properties of composition etc then - good luck!
The 'quality' of an image is not measurable, because it doesn't correspond to any particular value.
If u take it as number of pixels in the image of specific size its not accurate. You might talk about a photograph taken in bad light conditions as being of 'bad quality', even though it has exactly the same number of pixels as another image taken in good light conditions. This term is often used to talk about the overall effect of an image, rather than its technical specifications.
I wanted to do something similar, but wanted the "Soylent Green" option and used people to rank images by performing comparisons. See the question responses here.
I think you're asking about how to determine the quality of the compression process itself. This can be done by converting the JPEG to a BMP and comparing that BMP to the original bitmap from with the JPEG was created. You can iterate through the bitmaps pixel-by-pixel and calculate a pixel-to-pixel "distance" by summing the differences between the R, G and B values of each pair of pixels (i.e. the pixel in the original and the pixel in the JPEG) and dividing by the total number of pixels. This will give you a measure of the average difference between the original and the JPEG.
Reading the number of pixels in the image can tell you the "megapixel" size(#pixels/1000000), which can be a crude form of programatic quality check, but that wont tell you if the photo is properly focused, assuming it is supposed to be focused (think fast-motion objects, like trains), nor weather or not there is something in the pic worth looking at, that will require a human, or pigeon if you prefer.