Scaling image in R Last Updated : 06 Jun, 2021 Comments Improve Suggest changes Like Article Like Report In digital image processing or D.I.P., image scaling refers to the resizing of a digital image. Here, we are scaling an image using R Programming language. This is a subpart of the topic image transformations in digital image processing. If we are increasing the size of an image then it means that we are scaling it up and if we are decreasing or making the image the smaller, then it means we are scaling it down. Image in use: Method 1: Using OpenImageR First install OpenImageR package in Rstudio. OpenImageR is an image processing Toolkit that Incorporates functions for image preprocessing, filtering and image recognition. The image to be resized is imported to the environment and the required resizing is done using image_scale() function. The image_scale() function is a helper function to draw scale for image. It plots a scale in the right margin of a plot, typically an image plot. We will pass the image and the value as arguments in the function. Syntax: image_scale(img,"size") The only difference in scaling up or down comes from the size value passed to image_scale() function. To scale up down pass a value smaller than 100 and to up scale a value greater than 100. Program: R library(OpenImageR) img = image_read("gfg.png") image_scale(img,"30%") Output : Method 2: Using magick magick is a module in R programming language that provides modern and simple toolkit for image processing. The process completely similar to the above method the difference the package. image_scale() can also be used to resize image here too and can be deal with height and width at the same time. Syntax: image_scale( image_scale (image, "width"), "height") Example: R library(magick) img = image_read("gfg.png") image_scale(image_scale(img,"50%"),"80%") Output: Comment More infoAdvertise with us Next Article Divide Each Row of Matrix by Vector Elements in R M manikathuria2001 Follow Improve Article Tags : R Language R Programs Image-Processing Similar Reads Scaling a numeric matrix in R with values Scaling a numeric matrix in R Programming Language is a common preprocessing step in data analysis and machine learning. It involves transforming the data so that each column has a mean of zero and a standard deviation of one. This process, known as standardization or z-score normalization, helps br 3 min read Magrittr Package in R Programming If you have been using R programming for a while, you may have come across the magrittr package. This package is designed to make the process of writing R code more efficient and readable. In this article, we will discuss what the Magrittr package is, why it is useful, and how to use it in your R co 6 min read Divide Each Row of Matrix by Vector Elements in R In this article, we will discuss how to divide each row of the matrix by vector elements in R Programming Language. Method 1: Using standard division Initially, the transpose of the matrix is computed, to interchange the rows and columns. Initially, if the dimensions of the matrix were n * m , trans 6 min read Multidimensional Scaling Using R Multidimensional Scaling (MDS) is a technique used to reduce the dimensionality of data while preserving the pairwise distances between observations. It is commonly used in fields such as psychology, sociology, and marketing research to create visual representations of complex data sets. In this art 8 min read Scale Function in R Scale function in R is a handy way of accomplishing this goal. This means that the numerical variables are uniformized by means of centering and scaling. This piece goes into all the intricacies of the scale function such as its syntax, parameters, use, examples, applications, and best practices so 4 min read Feature Scaling Using R Feature scaling is a technique to improve the accuracy of machine learning models. This can be done by removing unreliable data points from the training set so that the model can learn useful information about relevant features. Feature scaling is widely used in many fields, including business analy 4 min read Like