Merge pull request #266 from sergiopaniego/small_typo

Small typo fixed

chapters/en/unit1/image_and_imaging/examples-preprocess.mdx

@@ -11,7 +11,7 @@ In digital image processing, operations on images are diverse and can be categor
 - Mathematical
 - Transform operations.
 
-Each category encompasses different techniques, such as morphological operations under logical operations or fourier transforms and principal component analysis (PCA) under transforms. In this context, we refer to morphology as the group of operations tha use structuring elements to generate images of the same size by looking into the values of the pixel neighborhood. Understanding the distinction between element-wise and matrix operations is important in image manipulation. Element-wise operations, such as raising an image to a power or dividing it by another image, involve processing each pixel individually. This pixel-based approach contrasts with matrix operations, which utilize matrix theory for image manipulation. Having said that, you can do whatever you want with images, as they are matrices containing numbers!
+Each category encompasses different techniques, such as morphological operations under logical operations or fourier transforms and principal component analysis (PCA) under transforms. In this context, we refer to morphology as the group of operations that use structuring elements to generate images of the same size by looking into the values of the pixel neighborhood. Understanding the distinction between element-wise and matrix operations is important in image manipulation. Element-wise operations, such as raising an image to a power or dividing it by another image, involve processing each pixel individually. This pixel-based approach contrasts with matrix operations, which utilize matrix theory for image manipulation. Having said that, you can do whatever you want with images, as they are matrices containing numbers!
 
 ## Mathematical Tools in Image Processing
 Mathematical tools are indispensable in digital image processing. Set theory, for instance, is crucial for understanding and performing operations on images, particularly binary images. In these images, pixels are typically categorized as either foreground (1) or background (0). In set theory, operations such as union and intersection determine relationships between features represented by pixel coordinates. Intensity transformations and spatial filtering are other mathematical tools. They focus on manipulating pixel values within an image, where operators are applied to single images or a set of images for various purposes, like noise reduction.