Histogram Equalization

Hey, I’m trying a histogram equalization. I’m getting the following error. Can someone please help me with this?
Thanks in advance!

Please make sure to post actual code rather than screenshots or literal photos of your screen, as it makes reading your question & helping you a lot more cumbersome!

That said the error you’re seeing is telling you that an index you are using is not an integer, but a floating point (decimal) number. This is likely in your call to cdf[image[i, j] + 1], where image[i, j] + 1 might be an integer?

Are you attempting to call the cdf function here? If so, use round brackets cdf(image[i, j] + 1) - in general, square brackets [] are for indexing, round brackets () are for calling.


Hey sorry for the picture.
Here is my code:
I have a histogram of the image,
hist = myHis(image)
cum = cumsum (hist)
cdf = cum ./ sum(cum) #type Array{Float64,1}

#for histogram equalization
m, n = size(image)
for I in 1: m-1
for j in 1: n-1
map[UInt8( [i,j] * 255)] = cdf(image[i,j] + 1)

I changed the square brackets to (). Now the error is “MethodError: objects of type Array {Float64, 1} are not callable. Use square brackets for indexing an array”

When I’m using square brackets, the error is “ArgumentError: invalid index: 1.3019608f0 of type Float32”


use triple backticks to surround your code…

in this code isn’t the outer loop variable an “ell” ( l ) not an “eye” ( i )
that’s your problem. you’re indexing with i

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Oops! Sorry It’s a typo. It’s actually “i”, not ell.

This line doesn’t make sense to me. I’m not even able to figure out what you’re trying to do here. Can you describe in words what you’re trying to do?

I’m mapping the pixel in the image to the new one.
(i,j) is the intensity of the particular rows and column. I’m casting it as an UInt8 using UInt8(). though it says UInt() I’m pretty sure the values are floating points (it was previously divided by 255 whatever) so I multiply it by 255 and then I cast it as UInt8.

Perhaps you meant map[i,j] =Uint8(cdf(image[i,j] +1)*255)

Isn’t that same? But I tried out and getting the same error “ArgumentError: invalid index: 1.3019608f0 of type Float32”

So cdf is apparently an array, and so is map? It’s easy to get confused, because those two are also the names of functions. In particular, I think you should change the name of the map array to make things less confusing.

Maybe you can try

map[i, j] = cdf[round(UInt8, image[i, j]) + 1] 

So here, cdf is not an in-built function. Cdf is actually from my code as follows:

cum = cumsum(histogram)
cdf = cum ./ sum(cum) 

Oh right! If I change my code like,

m, n = size(image)
for i in 1-m
      for j in 1-n
            out[i,j] = cdf [round(UInt8, image[i,j]) + 1]

So image[i,j] is Already a type of UInt8. I don’t think it’s okay to use round(UInt8, image[i,j) because it will throw an TypeError.

If image[i, j] is already of type UInt8 then it’s not necessary to round or convert it, but it should work. But why are you trying to change things into UInt8, then? Just try

map[i, j] = cdf[image[i, j] + 1]

I tried that out. It throws an error, “ArgumentError: invalid index: 1.3019608f0 of type Float32”

So I thought about converting it. So i casted UInt8, multiplying it by 255. Unfortunately, it throws the same error.

But then image isn’t a UInt8 array after all, but an array of Float32. Why can’t you use round like I suggested, then?

Typeof(image) is Array{Gray{Normed{UInt8,8}}, 2}

This is what I’m confused about.

Type of my histogram and cdf both are, Array{Float64, 1}

So I tried using round.() to my cdf, to convert it into UInt8. The plot is more like step side function, not a cumulative histogram.

So, the thing is, there’s apparently a lot of important information that we don’t have access to. In order to help, we need to know what all the different variables are, and what they mean. Perhaps you can read this PSA: make it easier to help you , before going further? Just the first post, not the whole thread.

well then,

julia> using Images, ImageView, Plots, ImageCore

#Histogram function 
julia>  function myHis(image)
        m, n = size(image)
        frequency = zeros(256)
            for i in 1:m, j in 1:n
                 frequency[UInt8(image[i,j] * 255)] += 1    
         return frequency ./ sizeof(image)

julia>  image = load("bookstore_dark.tif")
        hist = myHis(image)
        cum = cumsum(hist)
        cdf = cum ./ sum(cum)

#Histogram Equalization
julia>  m, n = size(image)
        for i in 1:m-1
            for j in 1:n-1
                out[UInt8([i,j] * 255)]= cdf[image[i,j]  + 1]
ArgumentError: invalid index: 1.3019608f0 of type Float32

 [1] to_index(::Float32) at .\indices.jl:297
 [2] to_index(::Array{Float64,1}, ::Float32) at .\indices.jl:274
 [3] to_indices at .\indices.jl:325 [inlined]
 [4] to_indices at .\indices.jl:322 [inlined]
 [5] getindex(::Array{Float64,1}, ::Float32) at .\abstractarray.jl:980
 [6] top-level scope at .\In[102]:4

Note that this code depends on a file local to your computer (bookstore_dark.tif), so it’s not possible for others to run.

That said, the problem still seems to be the one initially conjectured: your image object likely contains Float32 element, so when you do cdf[image[i, j] + 1] you are essentially trying to get the 1.3rd element of the cdf vector, which is not an operation that makes sense.

This isn’t the only issue in that loop though, as:

julia> UInt8([1,1]*255)
ERROR: MethodError: no method matching UInt8(::Array{Int64,1})
Closest candidates are:
  UInt8(::Union{Bool, Int32, Int64, UInt32, UInt64, UInt8, Int128, Int16, Int8, UInt128, UInt16}) at boot.jl:709
  UInt8(::Float32) at float.jl:686
  UInt8(::Float64) at float.jl:686

You can’t create an 8-bit unsigned integer from a vector. You might be trying to convert the vector into UInt8s, in which case you want to broadcast UInt8.([1,1]*255). Note however that idexing with UInt8 doesn’t work:

julia> rand(10, 10)[UInt8.([1,1]*255)]
ERROR: BoundsError: attempt to access 10×10 Array{Float64,2} at index [UInt8[0xff, 0xff]]
 [1] throw_boundserror(::Array{Float64,2}, ::Tuple{Array{UInt8,1}}) at ./abstractarray.jl:537
 [2] checkbounds at ./abstractarray.jl:502 [inlined]
 [3] _getindex at ./multidimensional.jl:726 [inlined]
 [4] getindex(::Array{Float64,2}, ::Array{UInt8,1}) at ./abstractarray.jl:980
 [5] top-level scope at REPL[19]:1

So given that you’re just using the result of this UInt8 construction to index your out array, it’s probably best to forget about this altogether.

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Where does out come from? It has to be initialized somewhere.

So your problem is indexing. We don’t know what your image is, so that makes it harder, but at least we can point out things that do not make sense:

If image is an array of floats, then UInt8(image[i,j] * 255) is unlikely to work, since UInt8 can only convert integer values:

julia> UInt8(1.0)  # this works

julia> UInt8(1.6)  # this doesn't works
ERROR: InexactError: UInt8(1.6)

Therefore I think you should round or truncate instead of convert:

julia> round(UInt8, 1.0)  # works

julia> round(UInt8, 1.6)  # works

julia> trunc(UInt8, 1.0)  # works

julia> trunc(UInt8, 1.6)  # works

In fact, when indexing you should normally just use Ints instead of UInt8.

So you can try

frequency[trunc(UInt8, image[i,j] * 255)] += 1

but, I got the impression that image[i,j] isn’t a normal float, but a RGB type, and I don’t know how to handle them.

Here you are trying to index into cdf using the contents of image[i,j], and since that is not an integer, you cannot use it for indexing.

And then there’s this:

Here you are trying to convert the vector [i, j] of Ints to UInt8. I don’t understand why you are trying to do that, since you can (and should) use ordinary Ints for indexing, and also because UInt8([i,j]*255) could never work anyway. [i,j]*255 is a vector, so then you would have to use UInt8.([i,j]*255), but even that wouldn’t work, because i*255 and j*255 is bigger than 255 except when i and j are 0 or 1.

1 Like

I understand now how it works. Thanks!
i just found i missed something in my histogram function.

  julia> function myHis(image)
           m, n = size(image)
           frequency = zeros(256)
        for i in 1:m, j in 1:n
        frequency[UInt8(image[i,j] * 255)+1 ] += 1   
    return frequency ./ sizeof(image)