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3D scatterplot of an image

alexander.engineering

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Re: 3D scatterplot of an image

#61

Post by [deleted] »

tovacinni wrote: post #60
thechao wrote: post #24

In the late '90s I was asked to do image segmentation of multispectral data of brightfield microscope data. That is, given a picture of a bunch of cells, find all of the cells. There were two problems: image segmentation of sick cells is really hard (they're very blobby & fragmented), and the computer I had available took more than 20 minutes per image. It was literally both cheaper and faster to have a grad student…

Sorry if this is a stupid question, but can't you do this without converting the image into an RGB 3D space? (i.e. iterate through the pixels and count the ones within a certain range of what you want)

[deleted]

Re: 3D scatterplot of an image

#63

Post by infinite8s »

tovacinni wrote: post #60
thechao wrote: post #24

In the late '90s I was asked to do image segmentation of multispectral data of brightfield microscope data. That is, given a picture of a bunch of cells, find all of the cells. There were two problems: image segmentation of sick cells is really hard (they're very blobby & fragmented), and the computer I had available took more than 20 minutes per image. It was literally both cheaper and faster to have a grad student…

Sorry if this is a stupid question, but can't you do this without converting the image into an RGB 3D space? (i.e. iterate through the pixels and count the ones within a certain range of what you want)

How would you determine if they were within the range? That's effectively converting it into a 3D space.

Re: 3D scatterplot of an image

#64

Post by zwieback »

crispyambulance wrote: post #25

This reminds me of a machine vision application for large-scale bakeries. When you bake bread, the color of the surface changes as the bread rises and completes the baking process. In the application I remember, the average color of a loaf was tracked on an RBG plot as a function of time. The idea was that the baking process followed a trajectory in the RGB space that was dependent on the temperature of the oven and…

I did the same thing for browning of french fries. It turned out that RGB was too highly correlated to be efficient so I mapped into an "application specific" color space where the rate was pretty much along a straight line. Kind of like HSV but more specific to the actual cucumber shape of the RGB distribution.

https://www.google.com/patents/US5818953

Re: 3D scatterplot of an image

#65

Post by crispyambulance »

yorwba wrote: post #56
seanlinehan wrote: post #45

Earlier quoted context omitted.

Do you have any examples of this? Sounds cool

I did a Jupyter notebook http://nbviewer.jupyter.org/github/Yorwba/image_frequency_sc... I should have probably written more comments, but I really need to go sleep now.

Yep, that's it! Here's the same thing in R...

  library(imager)
  download.file("https://upload.wikimedia.org/wikipedia/en/2/24/Lenna.png",'lena.png', mode = 'wb')
  
  lena

Re: 3D scatterplot of an image

#66

Post by adrianmonk »

_han wrote: post #53
adrianmonk wrote: post #43

"based on the pixel values" I daresay technically this applies to all useful visualizations of the data. I don't think they'd be very useful if they weren't, in some way, based on the pixel values.

Sure, but here the pixel values are directly used as spatial coordinates, so it makes sense to mention this.

I was trying to make a point about phrasing. "Based on" is wordy and nebulous. Just saying "of" would clearer, not to mention shorter.

Re: 3D scatterplot of an image

#67

Post by pavel_lishin »

abainbridge wrote: post #11
pavel_lishin wrote: post #3

This is cool, but I wonder why most of the demo images - and a lot of the images I uploaded - seem to have their colors aligned in a single plane.

Partly it is because real objects are often made out of a single colour. The camera sees different parts of the object under different lighting conditions. That mainly only changes the brightness. Specular highlights also desaturate the base colour, but nothing changes the hue. So all the pixels for that object tend to be aligned on a plane in the colour space plot. In the example images, the sand in the sand+sky pic…

But I'd expect to see distinct clumps, not a straight plane...

Re: 3D scatterplot of an image

#68

Post by ska »

psyklic wrote: post #55

There is a really cool use of clustering with these scatterplots to do color quantization (i.e. reducing the number of colors). If you want 16 colors, just find 16 clusters and their centroids (e.g. let k=16 for k-means clustering). Replace each pixel with the closest centroid. Then, your image is quantized (and can perhaps be stored more efficiently)!

There is nothing specific about color here - the same approach can be used for intensity re-quantization for example.

Effectively you are non-uniformly resampling based on distribution, so relative values/distances go out the window but you keep "detail" in the lower fidelity signal.

Re: 3D scatterplot of an image

#69

Post by abainbridge »

pavel_lishin wrote: post #67
abainbridge wrote: post #11

Earlier quoted context omitted.

Partly it is because real objects are often made out of a single colour. The camera sees different parts of the object under different lighting conditions. That mainly only changes the brightness. Specular highlights also desaturate the base colour, but nothing changes the hue. So all the pixels for that object tend to be aligned on a plane in the colour space plot. In the example images, the sand in the sand+sky pic…

But I'd expect to see distinct clumps, not a straight plane...

Imagine you have a flat red piece of card in a photographed scene. If the lighting is just right and the card is matt, you could get all the pixels of the card in the image to be the exact same colour. That would be a single point in the colour space.

Now imagine you rolled the card into a cylinder. The result would depend on the lighting, but most likely you'd be able to see some shading across the object, so that there are some darker and lighter pixels. In, the HSV colour space you'd now have a line - all the H and S values for those pixels would be the same, but there would be a range of values for V.

Now imagine you replaced the matt card with a shiny piece. You might see a whitish specular highlights where the object reflects a light source or the sky. The added whiteness would have made some pixels have a lower saturation (S). So now you have variation in S and V, but not H. That would form a plane in the HSV plot.

Re: 3D scatterplot of an image

#70

Post by pygy_ »

jpfed wrote: post #58
pavel_lishin wrote: post #3

This is cool, but I wonder why most of the demo images - and a lot of the images I uploaded - seem to have their colors aligned in a single plane.

Maybe planar colors make for better-looking images (a more cohesive feel) and the demo images were chosen because they look good.

That would have been my guess as well. I wouldn't have guessed that those paintings had such a planar palette

Well, not that flat actually, the way the image were processed also makes them flatter than they really are see

https://uploads2.wikiart.org/images/vincent-van-gogh/the-sta...

for example.

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