🌈 Image Color Histogram Viewer
Browser‑only histogram analyzer that extracts pixel data via Canvas, computes 256‑bin histograms per channel (R, G, B), and renders color‑coded charts. Great for exposure checks, palette analysis, and compression tuning.
RGB Histogram Preview:
How to Use This Image Color Histogram Viewer
The Image Color Histogram Viewer analyzes the distribution of pixel intensities across the red, green, and blue channels. It’s ideal for checking exposure, contrast, color cast, and palette balance—directly in your browser.
- Upload: Click Image File and choose a PNG/JPG/WebP/GIF.
- Generate: Press Generate Histogram to compute 256‑bin RGB histograms.
- Inspect: Review channel graphs, peaks, and overall distribution (shadows → highlights).
- Download: Save the histogram canvas for reports or documentation.
Tips:
- A left‑heavy graph indicates shadows; right‑heavy indicates highlights. Spikes can reveal posterization or strong tones.
- If channels are unbalanced (e.g., red shifted right), the image may have a color cast.
- Resize large images beforehand if your device is memory‑constrained.
How It Works
The viewer leverages the Canvas API to extract pixel data and compute histograms locally—no uploads or external libraries.
- Rasterization: The image is drawn to an off‑screen canvas at native size, then
getImageDataretrieves RGBA values. - Binning: For each pixel, the R/G/B values increment one of 256 bins (0–255). Alpha is ignored for histogram counts.
- Normalization: The highest bin per channel defines vertical scaling so all channels fit the canvas with clear contrast.
- Rendering: Bars are drawn per channel using semi‑transparent colors (red/green/blue) with optional overlay for combined view.
All processing is client‑side for speed and privacy. Very large images depend on available memory and GPU limits.
When You Might Need This
- • Photographers checking exposure and contrast before editing
- • Designers evaluating color balance across assets for brand consistency
- • Engineers analyzing palettes for compression or quantization
- • Data viz developers validating exported chart color distributions
- • Print workflows checking tonal range against paper limits
- • QA teams inspecting assets for banding or posterization
- • Content creators comparing thumbnails for visual punch
- • Researchers measuring channel skew in image datasets
- • Web teams assessing LQIP/placeholder characteristics
- • Educators demonstrating histograms in imaging courses
Frequently Asked Questions
What does the histogram show?
It shows how many pixels fall into each intensity bucket (0–255) for red, green, and blue channels. Left is dark, right is bright.
Why do I see spikes?
Spikes indicate many pixels sharing similar intensities—common with flat backgrounds, strong colors, or compressed gradients.
Are alpha pixels counted?
Alpha is ignored for counts; the viewer bins R, G, and B only. Transparent pixels still contribute their color values if present.
Will my image be uploaded?
No. All computation happens in your browser with the Canvas API; files never leave your device.
How big an image can I analyze?
Large images depend on device memory; if analysis fails, reduce dimensions and try again.