<p>I'm working in a computer vision project, where the goal is to detect some specific parasites, but now that I have the images, I noticed that they have a watermark that specifies the microscope graduation.
I have some ideas of how to remove this noise, like detecting the numbers and replace for the most common background or split the image but if I split the image I'll lose information.</p>

<p>But I would like to hear some recommendations and guidelines of experts. </p>

<p>I added an example image below.</p>

<p><a href="https://i.sstatic.net/lU8LQ.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/lU8LQ.png" alt="enter image description here"></a></p>

CC BY-SA 4.0
2019-04-10T00:03:55.570Z
it would make more sense to just crop the image so that the label is removed. why don't you do that instead?
k.c. sayz 'k.c sayz'
CC BY-SA 4.0
2019-04-10T00:10:52.560Z
Thanks for your comment, Yes but this is one optimal case, some labels are in different places
Erick Díaz
<convolutional-neural-networks><image-recognition><computer-vision>
How do I denoize a microscopic image?
Erick Díaz
# How do I denoize a microscopic image?

(Asked by: username_0 on 2019-04-09)

I'm working in a computer vision project, where the goal is to detect some specific parasites, but now that I have the images, I noticed that they have a watermark that specifies the microscope graduation.
I have some ideas of how to remove this noise, like detecting the numbers and replace for the most common background or split the image but if I split the image I'll lose information.

But I would like to hear some recommendations and guidelines of experts.

I added an example image below.

[![enter image description here](https://i.sstatic.net/lU8LQ.png)](https://i.sstatic.net/lU8LQ.png)

**Tags:** convolutional-neural-networks, image-recognition, computer-vision

> **Comments:**
> **username_1**: it would make more sense to just crop the image so that the label is removed. why don't you do that instead?  
> **username_0**: Thanks for your comment, Yes but this is one optimal case, some labels are in different places  

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## 0 answers

