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’ »
Posts tagged ‘SSE2’
Using SSE to process images or video is essential to achieving good performance. Most popular multimedia applications use SSE to greatly accelerate application performance. Unfortunately, like everything in life, if SSE is used incorrectly it can actually perform worse than non-SSE code. This article will take you through some code and discuss the performance of each. Continue reading ‘Image Processing with SSE’ »
The SSE instruction set can be a very useful tool in developing high performance applications. SSE, or Streaming SIMD Extensions, is particularly helpful when you need to perform the same instructions over and over again on different pieces of data. SSE vectors are 128-bits wide, and allow you to perform calculations for 4 different floating point numbers at the same time. SSE can also be configured to work on 2, 64-bit floating point numbers concurrently, 4, 32-bit integers, or even 16, 8-bit chars. Continue reading ‘Getting started with SSE programming’ »