Tag Archives: numpy

Gradient-descent optimized recursive filters for deconvolution / deblurring

Posted on September 5, 2022 by bartwronski

This post is a follow-up to my post on deconvolution/deblurring of the images. In my previous blog post, I discussed the process of “deconvolution” – undoing a known convolution operation. I have focused on traditional convolution filters – “linear phase, … Continue reading →

Posted in Code / Graphics | Tagged algorithms, digital signal processing, graphics, graphics programming, image processing, jax, maths, numpy, python, signal processing | Leave a comment

Superfast void-and-cluster Blue Noise in Python (Numpy/Jax)

Posted on April 21, 2021 by bartwronski

This is a super short blog post to accompany this Colab notebook. It’s not an official part of my dithering / Blue Noise post series, but thematically fits it well and be sure to check it out for some motivation … Continue reading →

Posted in Code / Graphics | Tagged blue noise, dithering, graphics programming, jax, numpy, python | 2 Comments

Bilinear down/upsampling, aligning pixel grids, and that infamous GPU half pixel offset

Posted on February 15, 2021 by bartwronski

It’s been more than two decades of me using bilinear texture filtering, a few months since I’ve written about bilinear resampling, but only two days since I discovered a bug of mine related to it. 😅 Similarly, just last week … Continue reading →

Posted in Code / Graphics | Tagged digital signal processing, gpu, image processing, libraries, numpy, sampling, signal processing, upsampling | 11 Comments

Converting wavetables to Ableton Operator AMS waves

Posted on January 5, 2021 by bartwronski

This blog post comes with Ableton Operator AMS “wavetables” here. In Ableton’s FM synth you can use different types of oscillator waves as your operators (both carriers as well as modulators), as well as draw custom ones: What is not … Continue reading →

Posted in Audio / Music / DSP | Tagged ableton, digital signal processing, dsp, fourier, frequency domain, numpy, python, synthesis | 3 Comments

“Optimizing” blue noise dithering – backpropagation through Fourier transform and sorting

Posted on April 26, 2020 by bartwronski

Introduction This will be a blog post that is second in an (unanticipated) series on interesting uses of the JAX numpy autodifferentiation library, as well as an extra post in my very old post series on dithering in games and … Continue reading →

Posted in Code / Graphics | Tagged blue noise, dithering, frequency domain, image processing, jax, machine learning, noise, numpy, python | 6 Comments

Using JAX, numpy, and optimization techniques to improve separable image filters

Posted on March 15, 2020 by bartwronski

In today’s blog post I will look at two topics: how to use JAX (“hyped” new Python ML / autodifferentiation library), and a basic application that is follow-up to my previous blog post on using SVD for low-rank approximations and … Continue reading →

Posted in Code / Graphics | Tagged bokeh, colab, github, graphics programming, image processing, jax, machine learning, maths, numpy, postprocessing, programming, python | 11 Comments

Separate your filters! Separability, SVD and low-rank approximation of 2D image processing filters

Posted on February 3, 2020 by bartwronski

In this blog post, I explore separable convolutional image filters: how can we check if a 2D filter is separable, and how to compute separable approximations to any arbitrary 2D filter represented in a numerical / matrix form using SVD. Continue reading →

Posted in Code / Graphics | Tagged algorithms, approximation, blur, bokeh, depth of field, graphics, image processing, linear algebra, numpy, optimizations, postprocessing, python | 15 Comments

Analyze your own activity data using Google Takeout – music listening stats example

Posted on January 6, 2020 by bartwronski

The goal of this post is to show how to download our own data stored and used by internet services to generate personalized stats / charts like below and will show step-by-step how to do it using colab, Python, pandas, … Continue reading →

Posted in Code / Graphics | Tagged colab, data, numpy, programming, python, statistics, visualization | Leave a comment