# CLAHE Histogram Equalization

Apply Contrast Limited Adaptive Histogram Equalization for local contrast enhancement

> Canonical page: https://elysiatools.com/en/tools/image-clahe

- **Category:** Design

- **Keywords:** image, clahe, histogram, equalization, contrast, adaptive, local, enhancement, limit

## Overview

Enhance the visual clarity of your images using Contrast Limited Adaptive Histogram Equalization (CLAHE). This tool improves local contrast by dividing images into tiles, allowing you to reveal hidden details in underexposed or low-contrast areas without over-amplifying noise.

## Inputs

- **Image File** (file): Upload any image file (JPEG, PNG, WebP, GIF, BMP, TIFF) to apply CLAHE histogram equalization
- **Tile Size** (range): Size of tiles for local histogram equalization. Smaller tiles provide more local contrast enhancement
- **Contrast Limit** (range): Contrast amplification limit. Higher values allow stronger contrast enhancement but may amplify noise
- **Brightness Limit** (range): Brightness amplification limit. Lower values prevent over-amplification of bright areas
- **Grid Size** (range): Number of grid divisions. Higher values create more tiles for finer local enhancement
- **Output Format** (select): Choose output format or keep original. PNG recommended for maximum quality
- **Quality (1-100)** (number): Output quality for lossy formats (JPEG, WebP). Higher = better quality but larger file size

## When to use

- Improving visibility in medical or scientific imagery where subtle details are obscured by low contrast.
- Restoring clarity to photos taken in challenging lighting conditions, such as deep shadows or hazy environments.
- Preparing images for computer vision tasks by normalizing contrast across different regions of a frame.

## How it works

- Upload your image file in any standard format like PNG, JPEG, or TIFF.
- Adjust the Tile Size and Grid Size to define the local area for contrast calculation.
- Fine-tune the Contrast Limit and Brightness Limit to balance enhancement strength against potential noise.
- Select your preferred output format and quality settings, then download the processed image.

## Use cases

- Enhancing medical X-rays or scans to better visualize tissue structures.
- Correcting underexposed landscape photography to bring out shadow detail.
- Preprocessing surveillance footage to improve object detection in low-light conditions.

## Frequently asked questions

### What is CLAHE?

CLAHE stands for Contrast Limited Adaptive Histogram Equalization. It is an image processing technique that enhances contrast locally rather than globally, preventing the over-amplification of noise.

### How does the Tile Size affect my image?

Smaller tile sizes provide more localized contrast enhancement, which is great for fine details, while larger tiles provide a smoother, more global-like adjustment.

### Will this tool increase image noise?

High contrast limit settings can amplify noise. If your image appears grainy after processing, try lowering the Contrast Limit value.

### Which file formats are supported?

You can upload JPEG, PNG, WebP, GIF, BMP, and TIFF files. You can also choose to convert your output to a different format.

### Is there a limit to the file size?

Yes, the tool supports individual image files up to 20MB.

## Related tools

- [Image Adaptive Threshold](https://elysiatools.com/en/tools/image-adaptive-threshold): Apply adaptive threshold operation that calculates threshold for small regions, suitable for varying lighting conditions
- [Image Color Burn Blend](https://elysiatools.com/en/tools/image-color-burn): Apply color burn blend mode between two images for dramatic darkening and intense color effects
- [Image Gradient Operation](https://elysiatools.com/en/tools/image-gradient): Apply gradient operations (Sobel, Prewitt, Roberts) for edge detection and image enhancement
- [Image Hard Light Blend](https://elysiatools.com/en/tools/image-hard-light): Apply hard light blend mode between two images for strong, intense contrast and vivid effects
- [Image Laplacian Operator](https://elysiatools.com/en/tools/image-laplacian): Apply Laplacian operator for edge detection, sharpening, and image enhancement with different kernel variants
- [Image Soft Light Blend](https://elysiatools.com/en/tools/image-soft-light): Apply soft light blend mode between two images for gentle, subtle contrast enhancements
- [Bilateral Filter](https://elysiatools.com/en/tools/image-bilateral-filter): Apply bilateral filter for edge-preserving smoothing that reduces noise while maintaining image details
- [Image Box Blur](https://elysiatools.com/en/tools/image-box-blur): Apply box blur kernel for simple uniform averaging and fast noise reduction

## Samples

- [Web Image Processing Python Samples](https://elysiatools.com/en/samples/web-image-processing-python): Web Python image processing examples using PIL/Pillow including reading, saving, resizing, and format conversion
- [Web Image Processing TypeScript Samples](https://elysiatools.com/en/samples/web-image-processing-typescript): Web TypeScript image processing examples including image read/save, scaling, and format conversion
- [Android Image Processing Java Samples](https://elysiatools.com/en/samples/android-image-processing-java): Android Java image processing examples including reading/saving images, scaling, and format conversion
- [Android Image Processing Kotlin Samples](https://elysiatools.com/en/samples/android-image-processing-kotlin): Android Kotlin image processing examples including reading/saving images, scaling, and format conversion