Natural MatchSubtle
Wedding portrait in warm amber tones
A daylight wedding portrait takes on the reference’s warm amber highlights and deep green shadows with Natural Match at Subtle strength.
AI-powered color grading
AI Color Match – Match Colors Between Images
Match the colors, lighting, and visual mood of one photo to another using AI.
AI Color MatchYour images are processed only when you generate.
A real output preview. Add your target and reference to create your own match.
Output quality
2K · AutoThe model selects the output dimensions. The exact size is shown with your result.
Each generation costs 12 credits
AI Color Match Examples
Explore how a target photo can take on a reference image’s colors and mood, with natural or creative AI editing.
Natural MatchSubtle
A lakeside moment in turquoise
A swan and its cygnets on a quiet lake take on turquoise water and deeper cool shadows inspired by the river reference, using Natural Match at Subtle strength.
Natural MatchSubtle
A watch in violet studio light
A neutral watch product photo takes on violet tones and blue-red reflections inspired by a lens-filter reference, using Natural Match at Subtle strength.
Natural MatchSubtle
A living room in warm amber
A bright living room takes on warm amber light and rich brick-red tones inspired by a candlelit reference, using Natural Match at Subtle strength.
How to Match Colors Between Images
Keep the scene you love. Borrow a new color direction.
Upload Your Photo
Add your target photo: the subject and scene you want to keep. Use a still JPG, PNG, or WebP image.
Add a Reference Image
Choose the colors and mood you want to borrow. Select Natural or Creative Match and a strength.
Match Colors and Download
Sign in, check the credit cost, then select Match Colors. Review the result and download PNG, JPG, or WebP.
Natural Match vs Creative Match
Natural Match
Match the reference colors while aiming to preserve the original photo’s appearance and details.
- Prioritize the original scene and composition
- Aim for realistic color grading and restrained lighting
- Minimize unwanted changes to subjects and details
Best for portraits, products, and realistic photography.
Creative Match
Create expressive color grading and cinematic mood inspired by the reference image.
- Explore stronger cinematic palettes
- Allow more expressive lighting and atmosphere
- Aim to keep subjects and composition recognizable
Best for artistic photography and social content.
AI Color Match Features
Guided by your reference
Use a real photo to guide palette, warmth, contrast, and visual mood.
Two editing directions
Choose a restrained Natural Match or a more expressive Creative Match.
Adjustable strength
Subtle, Balanced, and Strong describe the intended intensity of the edit, not fixed percentages.
Content preservation goals
Instructions prioritize the target’s subjects, composition, text, and detail. Always review the output.
Model-native output
Generate with the model’s automatic 2K-class setting and see the actual output dimensions.
Flexible image downloads
Review your result online and export PNG, JPG, or WebP with the shared format picker.
AI Color Matching Use Cases
Portrait Photography
Explore a cohesive color mood across a portrait series.
Product Photography
Explore a consistent campaign look while checking important product colors.
Landscape Photography
Bring a reference’s warmth, cool tones, or cinematic atmosphere to your scene.
Interior Photography
Explore tonal harmony across architectural and interior photography.
Social Media Content
Explore a consistent palette for a post series or a visual campaign.
Creative & Cinematic Photography
Try expressive highlight colors, shadow tones, and atmosphere with Creative Match.
AI Color Match vs Traditional Filters
A filter applies a preset look. EzColorize uses AI image editing rather than histogram matching or traditional color transfer algorithms. A reference photo is used to guide the palette, warmth, contrast, and mood of your target. Results can vary: review faces, product colors, fine detail, and readable text before using an edited image.
Frequently Asked Questions
What is AI color matching?
AI color matching edits a target photo using another image as a palette and mood reference. It aims to adapt colors and tones while keeping the target’s essential scene content.
How do I match colors between two photos?
Upload the photo you want to edit as Target Image, add a Color Reference, choose a mode and strength, then sign in and review the cost notice before selecting Match Colors. The result depicts the target, not the reference.
What is the difference between Natural Match and Creative Match?
Natural Match aims for realistic grading and conservative lighting changes. Creative Match allows stronger colors and atmosphere while aiming to retain recognizable subjects and composition.
Will AI change the people or objects in my photo?
It can. Preservation is an instruction, not a guarantee. Inspect faces, objects, product colors, readable text, logos, and fine detail before using an edited image.
Can I use a reference image to match photo colors?
Yes. The reference is intended to guide color temperature, palette, contrast, and mood. It should not replace the target scene or copy the reference’s subjects. Use photos you have permission to upload.
What image formats are supported?
Upload still JPG, PNG, or WebP files up to 20 MB and 40 megapixels, with no side longer than 16,000 pixels. Inputs are validated and normalized for processing. Downloads support PNG, JPG, and WebP.
Is AI Color Match free?
Each generation uses 12 purchased credits and requires sign-in. Credits are reserved while processing, charged on success, and released if the edit fails. Daily free credits apply to Photo Colorizer V1. Trying an example does not generate an image or use credits.
Can I download high-resolution results?
Yes. The current model uses its automatic 2K-class output setting; exact dimensions depend on the returned image and are shown in the result. The download picker exports at the result’s dimensions. PNG retains the stored result, while JPG and WebP may use lossy encoding.