Denoising
Denoising is the iterative process by which a diffusion model removes random noise from an image step by step, guided by your prompt, until a clear picture emerges.
June 16, 2026
Denoising is the step-by-step process a diffusion model uses to transform random noise into a clear image guided by your prompt.
How it works
Diffusion models are trained by taking real images and gradually adding noise until they become pure static, then learning to reverse that process. To generate, the model starts from a field of random noise and predicts what to remove at each step. Across many small steps, the noise is peeled away and structure emerges — first rough shapes, then forms, then fine detail — all steered toward your text prompt. This reverse-noise loop is denoising, and it is the heart of how modern AI image generation works.
In image-to-image workflows, a related control called denoising strength decides how much of an existing picture the model overwrites. A low strength preserves the original composition and only refines it; a high strength treats the input as a loose suggestion and largely reinvents it.
Why it matters
Denoising explains the entire generation pipeline: an image is not painted in one shot but resolved gradually out of noise. The number of denoising steps affects detail and speed, while denoising strength governs how much an input image is respected — making it the key dial in editing-style and variation workflows. Understanding it clarifies why generation takes the form of a progressive refinement rather than an instant render.
In eaxy
eaxy runs the denoising loop for you with optimized step counts and samplers, so prompts resolve into sharp, faithful images in seconds. You see the finished result, not the noisy intermediate stages, and never need to tune step or strength settings by hand.
Related terms
Frequently asked questions
What is denoising in AI image generation?+
It is the core generation process: the model starts from random noise and removes it in successive steps, guided by your prompt, until a coherent image appears.
What is denoising strength?+
In image-to-image, denoising strength sets how much of the starting image is overwritten. Low strength keeps it close to the original; high strength lets the model reinvent it more freely.
How many denoising steps are needed?+
More steps can refine detail up to a point, then add little. Modern models and samplers produce strong results in relatively few steps, balancing quality and speed.
Do I control denoising in eaxy?+
No. eaxy manages steps and denoising strength automatically so you get sharp, prompt-accurate images in seconds without tuning sampler settings.
Make it with eaxy
Describe anything and generate stunning images in seconds — then bring them to motion with Kling 3.