Posts tagged ‘Image processing’

When performing image transformation and manipulation techniques, it is often necessary to employ some sort of interpolation or filtering in order to obtain a good image quality. For example, if you scale an image, you can determine the final color of each pixel by either some basic nearest neighbor method, or a more advanced interpolation method. However, an interpolation method will invariably offer better final image quality. In this tutorial, we’ll be writing a function to rotate an image, using bilinear interpolation. This tutorial also demonstrates how to perform a high quality image rotate transformation, however, that is not the focus of this tutorial, but rather the example transform being performed. Continue reading ‘Coding Bilinear Interpolation’ »

In a previous article about image processing with SSE, we used some basic SSE intrinsics to perform a very easy image manipulation routine, removing all blue from an image. This task was easy, since each pixel was 8 bits per component, with 4 components (ARGB). However, for more advanced image processing functions such as 2D convolution, it is preferable to work with each color component as a 32-bit floating point number rather than an 8-bit unsigned integer. Continue reading ‘Advanced Image Processing with SSE’ »

In the previous tutorial, intro to image processing with CUDA, we examined how easy it is to port simple image processing functions over to CUDA. In this tutorial, we’ll be going over a substantially more complex algorithm, and how to port it to CUDA with incredible ease. Continue reading ‘Advanced Image Processing with CUDA’ »

CUDA is great for any compute intensive task, and that includes image processing. In this tutorial, we’ll be going over why CUDA is ideal for image processing, and how easy it is to port normal c++ code to CUDA. Continue reading ‘Intro to image processing with CUDA’ »

Image warps and other distortions are significantly more complicated than simple image processing techniques such as convolution. This tutorial will cover how to twist an image in the center. This exact code can be modified to do twists or other types of image warps. Continue reading ‘Image twist and swirl algorithm’ »

Taking an image and making it look like an oil painting is not only visually impressive, but also easy, from an algorithmic point of view. This page will show you how to write code to achieve the oil painting effect.

Continue reading ‘Oil Painting Algorithm’ »

Image convolution is the most vital image processing algorithm available. Using simple 2-D convolution, you can blur, sharpen, emboss, and even detect edges in an image. Not only is convolution so powerful, but it is also very easy to perform. Simply put, the value of a modified pixel is determined solely by it’s original value summed up with weighted values of it’s neighboring pixels. After the weighted sum is completed, a division takes place to normalize the value of the pixel, usually so that the brightness of the image remains the same. Sometimes, an offset can be added after the normalization for certain effects. Continue reading ‘Image Convolution with GDI+’ »

Writing raw C++ code to read a JPG or JPEG image can be a cumbersome task. Fortunately, libraries exist which we can use to perform the dirty work for us. In this tutorial, we will be using the GDI+ interface to easily read image files and draw them onto the window. In you are unfamiliar with GDI+, I would suggest you take a look at my previous tutorial on how to get up and running with GDI+. Please note that this tutorial is aimed for Windows programs only, since GDI+ is not available on other platforms. Continue reading ‘How to load a JPG with C++’ »

This tutorial will focus on how to create and compile an application that uses GDI+. We will be starting a project from scratch using Microsoft Visual Studio. GDI+ is a powerful, object oriented API for doing mostly 2D graphics. Unlike GDI, GDI+ is generally much easier to use, much more difficult to misuse, and in many cases can produce higher quality images than GDI. While GDI+ is considered slower than GDI, it is still perfectly acceptable for most applications. Continue reading ‘Getting started with GDI+ in Visual Studio’ »