Codetown ::: a software developer's community
Part 1: https://codetown.com/group/kotlin/forum/topics/kotlin-thursdays-ima...
Part 2: https://codetown.com/group/kotlin/forum/topics/kotlin-thursdays-ima...
Welcome to Kotlin Thursdays! Last week, we figured out how to write primitive filters and apply them to our images with the or function. This week, we look at refactoring with higher-order functions.
Think of these resources as supplemental if you happen to be more curious. We always encourage looking into documentation for things you use!
We could continue to write individual functions that feeds 2 images and a particular function, but in Kotlin, we have the ability to use a single function that accepts 2 images and a function with the help of higher order functions. Below, you can see how similar our orFilter function and makeDuller function is.
In programming, programs may take data as parameters and pass those parameters into the function to return a different output or alter the behavior of a program. Kotlin is a functional language, and one characteristic of a functional language is that functions are also able to treat functions as data. You can pass a function as a parameter, which is really powerful!
A higher-order function is a function that may take functions as parameters. You can pass a function with double-colon (::). Double-colon (::) is used to get function (callable) reference in Kotlin.
Ruby facilitates higher order functions with yield, which involves passing a block to a method.
Like Ruby, Kotlin treats functions as first-class citizens, which is a pillar of functional programming. In Kotlin, the equivalent of block code is known as lambda functions, indicated by the pattern:
Instead of passing the object as an argument, you invoke the lambda variable as it if were an extension function. Haskell also has higher order functions which can designate the kinds of parameters a function may take within a function.
In this case, we are going to work with a general function, as opposed to an extension function that is invoked with a qualifer.
The function we write will take a filter function and 2 pixelReaders. Our function parameter, in particular, will only accept functions that take 2 Color parameters and returns a Color.
So here, the input function that accepts the 2 parameters is the receiver type, the output Color receiver object.
fun applyFilter (filter: (Color, Color) --> Color, a: PixelReader, b: PixelReader): PixelWriter {
for (x in 0 until width) {
for (y in 0 until height) {
resultWriter.setColor(x, y, filter(a.getColor(x, y), b.getColor(x, y))
}
}
return resultWriter
}
I hope you all had fun learning a little bit about image processing! Keep exploring and creating new image filters and maybe even as a challenge, think about how you might implement an RGB system to create image filters for colors. Until next time :)
Tags:
Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.
Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
Check out the Codetown Jobs group.

At AWS re:Invent 2025, AWS expanded its Well-Architected Framework with a new Responsible AI Lens and updated Machine Learning and Generative AI Lenses. The updates provide guidance on governance, bias mitigation, scalable ML workflows, and trustworthy AI system design across the full AI lifecycle.
By Leela Kumili
Introducing oRPC 1.0, a cutting-edge TypeScript library for building typesafe APIs, offering a stable, production-ready solution with full OpenAPI integration. Key features include enterprise-grade type safety, complex type support, and seamless integration with popular frameworks. With superior performance and comprehensive migration guides, oRPC emerges as a choice for modern API development.
By Daniel Curtis
At QCon AI NY 2025, LinkedIn's Prince Valluri and Karthik Ramgopal unveiled an internal platform for AI agents, prioritizing execution over intelligence. By using structured specifications within a robust orchestration layer, they enhance agent observability and interoperability while ensuring human accountability.
By Andrew Hoblitzell
Pinterest published a technical case study detailing how its engineering team cut Android end-to-end (E2E) continuous integration (CI) build times by more than 36 percent by adopting a runtime-aware test-sharding strategy and building an internal testing platform.
By Craig Risi
Clara Matos discusses the journey of shipping AI-powered healthcare products at Sword Health. She explains how to implement input/output guardrails for regulated industries and shares a framework for robust evaluations using human and LLM-based ratings. From prompt engineering to RAG and user feedback loops, she shares a data-driven roadmap for building reliable AI care agents at scale.
By Clara Matos
© 2025 Created by Michael Levin.
Powered by