SampleYogiSampleYogi

Noise/Static Image Generator

Generate random noise and static images for testing, textures, overlays, and creative effects.

Generated locally in your browser

Ready-to-Download Samples

Download pre-built sample files instantly. No configuration needed.

Static Noise 320×240

43.9 KB

Classic TV snow pattern (QVGA)

Static Noise

Static Noise 640×480

175.8 KB

VGA static noise pattern

Static Noise

Static Noise 1280×720 (HD)

527.3 KB

HD static noise pattern

Static Noise

Static Noise 1920×1080 (FHD)

1.1 MB

Full HD static noise pattern

Static Noise

Perlin Noise 256×256

63.5 KB

Smooth procedural noise texture

Perlin Noise

Perlin Noise 512×512

253.9 KB

Medium Perlin noise texture

Perlin Noise

Create Custom File

Configure your own file with custom settings and content

Image Dimensions
Set the width and height of the noise image

Image width in pixels (1-4096)

Image height in pixels (1-4096)

Noise Settings
Configure the type and density of noise

Type of noise pattern to generate

Noise intensity/density (10-100%)

Grayscale or full color noise

Advanced
Additional options for reproducible results

Set a seed for reproducible noise patterns (optional)

Generate random noise and static images for testing, textures, and creative effects. Create classic TV static, smooth Perlin noise, film grain overlays, and more.

What is Noise/Static?

Digital noise consists of random variations in brightness and color. Static (TV snow) uses uniform random distribution, while Perlin noise provides smooth, natural-looking variations. These patterns are useful for testing, textures, and visual effects.

Why Use Noise Images?

Test image processing and compression algorithms with random data

Create texture overlays for film grain and vintage photo effects

Generate seamless tiling textures for games and 3D graphics

Test display quality and pixel response at various noise levels

Add organic imperfections to digital designs

Common Use Cases

Compression Testing

Noise images are difficult to compress, making them ideal for testing codec efficiency and image quality.

Film & Video Effects

Add film grain overlays to give digital footage a cinematic, analog appearance.

Game Development

Generate Perlin noise for terrain heightmaps, cloud textures, and procedural content.

Display Testing

Evaluate monitor pixel response, dead pixels, and color accuracy with random patterns.

Features

Multiple noise types (static, Perlin, grain)

Adjustable density (10-100%)

Grayscale and color modes

Reproducible patterns with seed values

Custom dimensions up to 4096×4096

Film grain and texture presets

Instant browser-side generation

Download as PNG format

How It Works

1

Configure

Customize your file settings using the form above

2

Preview

See your changes in real-time in the preview panel

3

Download

Download your file instantly - no signup required

Frequently Asked Questions

What is the difference between static and Perlin noise?

Static noise (TV snow) uses uniform random distribution where each pixel is independent. Perlin noise creates smooth, coherent variations that flow naturally between values, making it suitable for organic textures like clouds, terrain, and marble.

What density setting should I use?

For film grain effects, use 20-40% density. For testing or texture generation, 50% provides balanced noise. Use 80-100% for maximum random variation in compression testing or extreme visual effects.

How do I create a seamless tileable noise texture?

Use Perlin noise at power-of-2 dimensions (256×256, 512×512, 1024×1024). Perlin noise naturally tiles when generated at these sizes, making it ideal for game textures and repeating patterns.

What is the random seed used for?

The seed value initializes the random number generator. Using the same seed always produces the same noise pattern, allowing you to reproduce specific results or compare noise effects consistently.

Why are noise images hard to compress?

Compression algorithms work by finding patterns and redundancy in data. Random noise has no patterns, so each pixel must be stored individually. This makes noise images useful for testing maximum file sizes and codec limits.