Drop image here
or click to browse — JPG, PNG, GIF, WebPRGB Histogram will appear here
Upload an image and click Analyze// analyze rgb color distribution of any image
Analyze the color distribution of any image with an RGB histogram. Visualize red, green, blue, and luminance channels instantly in your browser.
Drop image here
or click to browse — JPG, PNG, GIF, WebPRGB Histogram will appear here
Upload an image and click AnalyzeDrop any image file or click the upload zone to browse. JPG, PNG, GIF and WebP are supported.
Toggle R, G, B or Luminance channels to customize which distributions are shown in the histogram.
Click Analyze to render the histogram. Save it as a PNG image for reports or documentation.
An image histogram shows the distribution of pixel intensity values (0–255) across each color channel. The X axis represents brightness levels from black (0) to white (255); the Y axis shows how many pixels have that value. Peaks indicate dominant tones in the image.
An image histogram is a graphical representation of pixel intensity distribution across tonal values (0–255). It shows how many pixels in an image have each brightness level, giving you insight into exposure, contrast, and color balance.
No. All processing happens entirely in your browser using the HTML5 Canvas API. Your image never leaves your device, making this tool completely private and safe for sensitive images.
The luminance (L) channel represents the overall brightness of each pixel calculated from a weighted average of red, green, and blue values (0.299R + 0.587G + 0.114B). It approximates human perception of brightness.
The tool supports any image format your browser can natively decode, including JPG, PNG, GIF, WebP, BMP, AVIF, and SVG. Simply drag and drop or click to browse for your file.
Peaks on the left indicate dark/shadow areas; peaks on the right indicate bright/highlight areas. A well-exposed image typically has values spread across the full range. Peaks clustered at the extremes may indicate under- or over-exposure.
Yes, though very large images (above 20MP) may take a moment to process. The tool samples all pixels for accuracy. For speed, images are rendered in a downscaled preview while the full-resolution data is used for histogram calculations.
An image histogram viewer is a tool that analyzes every pixel in a digital image and plots the frequency of each intensity value (from 0 to 255) for each color channel. The result is a graph — the histogram — that gives photographers, designers, and developers an immediate visual summary of an image's tonal range, color balance, and exposure characteristics. Our free browser-based histogram viewer supports red, green, blue, and luminance channels, and works entirely on your device without any uploads.
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The horizontal axis of a histogram spans from 0 (pure black) on the left to 255 (pure white) on the right. The vertical axis shows how many pixels in the image carry that exact intensity value. A tall spike at a particular value means a large number of pixels share that brightness level in that channel.
Each channel tells you something different:
Learning to read histogram shapes helps you quickly diagnose image quality issues:
Histogram analysis is useful far beyond just photography. Here are common use cases:
When you upload an image, the tool draws it onto an HTML5 Canvas element. Using the getImageData() API, it reads every pixel's RGBA values directly from memory. For each pixel, it increments a counter in a 256-element array for the red, green, and blue channels, and computes a luminance value using the standard ITU-R BT.601 formula: L = 0.299R + 0.587G + 0.114B.
Once all pixels are counted, the arrays are normalized to the maximum value so the histogram fits the canvas height. The resulting bars are then drawn using overlapping semi-transparent fills for each channel, creating the familiar multi-channel histogram seen in professional editing software. Dominant colors are extracted by clustering pixel values into buckets and selecting the most populated ones.
A histogram and a color palette answer different questions. A color palette tells you which specific hues are most prominent in an image (e.g., "#3a5f8a" appears 12% of the time). A histogram tells you how the raw intensity values are distributed across each channel. Both are useful — the histogram is better for assessing exposure, contrast, and channel balance, while a palette is better for brand matching, UI design, and visual theming.
This tool operates entirely in your web browser. No image data, pixel values, or metadata is ever sent to any server. The analysis is performed using the HTML5 Canvas API and JavaScript, making it safe to use with confidential images, internal screenshots, or personal photos. You can verify this by checking your browser's network requests — you'll see none related to your image after the page loads.