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Category Image Converters

Drop JPG images here or click to browse Supports JPG, PNG, WebP, GIF, BMP • No upload • 100% local

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About

JPEG compression operates on a lossy Q factor ranging from 1 (maximum compression, severe artifact introduction) to 100 (near-lossless, minimal size reduction). Selecting an inappropriate quality level risks either bloated file sizes that slow page loads and consume storage, or visible blockiness from aggressive quantization of DCT coefficients. This tool re-encodes every pixel through the browser's native JPEG codec at your specified Q, producing real output files with accurate byte counts. No server upload occurs. All processing runs locally via the Canvas API.

The default value of 85 typically yields a 40 - 60% size reduction with negligible perceptual loss for photographic content. Below 50, chroma subsampling artifacts become visible on sharp edges and text overlays. This tool approximates ImageMagick's -quality flag behavior, but quantization tables differ slightly between browser engines (Chromium vs. Firefox). Pro tip: process a single test image first and inspect the preview before committing to a full batch.

Formulas

The JPEG encoder applies Discrete Cosine Transform to each 8×8 pixel block, then quantizes coefficients using a quality-dependent quantization matrix. The effective compression ratio relates to quality as follows:

R = 1 − S_outS_in

where R = compression ratio (as fraction saved), S_out = output file size in bytes, S_in = input file size in bytes.

The browser's Canvas API encodes via:

canvas.toBlob(callback, "image/jpeg", Q100)

where Q = user-specified quality (1 - 100), divided by 100 to produce the 0.0 - 1.0 float the API expects. The quantization step size for each DCT coefficient k is approximately:

q_k = max(1, floor(T_k ⋅ S100))

where T_k = base quantization table value, S = scale factor derived from Q. When Q < 50, S = 5000Q. When Q ≥ 50, S = 200 − 2Q.

Reference Data

Quality Level	Typical Compression Ratio	File Size (per 12MP photo)	Perceptual Quality	Best Use Case
100	2:1	~5.5 MB	Indistinguishable from source	Archival, medical imaging
95	4:1	~3.0 MB	Excellent	Print production, photography portfolio
90	6:1	~2.0 MB	Very good	High-quality web images
85	8:1	~1.5 MB	Good (default sweet spot)	General web use, CMS uploads
80	10:1	~1.2 MB	Good, minor softness	E-commerce product images
75	12:1	~1.0 MB	Acceptable	Blog posts, social media
70	15:1	~800 KB	Noticeable softening	Email attachments, thumbnails
60	20:1	~600 KB	Visible artifacts on edges	Low-bandwidth applications
50	25:1	~480 KB	Obvious blocking	Preview/draft quality
40	30:1	~400 KB	Severe artifacts	Placeholder images
30	40:1	~300 KB	Heavy degradation	Bandwidth-critical mobile
20	55:1	~220 KB	Barely recognizable detail	Extreme compression tests
10	80:1	~150 KB	Abstract/mosaic appearance	Artistic effect, watermarks
1	100+:1	~80 KB	Unrecognizable	Minimum viable data

Frequently Asked Questions

The quality parameter Q controls the quantization matrix scaling. At Q = 100, quantization divisors approach 1, preserving nearly all DCT coefficients. At Q = 50, the standard JPEG quantization table is used unmodified. Below 50, divisors scale up rapidly (S = 5000/Q), aggressively zeroing high-frequency coefficients. The relationship is non-linear: the perceptual difference between Q = 90 and Q = 80 is far smaller than between Q = 20 and Q = 10.

Each JPEG encode-decode cycle introduces generation loss. The DCT transform is lossy due to quantization rounding. Re-encoding at the same quality Q does not preserve the original - each pass rounds coefficients again, accumulating error. If your source is already JPEG, converting at Q ≥ 95 minimizes additional degradation. Converting at a quality higher than the source's original quality will not recover lost data; it only increases file size.

No. The Canvas API strips all EXIF data (camera model, GPS coordinates, orientation, color profile) during re-encoding. If metadata preservation is critical, use a desktop tool like ImageMagick or ExifTool. The orientation tag loss can cause images to appear rotated; this tool compensates by reading orientation before processing and applying the correct canvas transform.

Practical limits depend on available RAM. Each image is decoded to raw RGBA pixels (4 bytes per pixel). A 12MP image (4000×3000) consumes approximately 48 MB in memory. Processing 50 such images simultaneously would require ~2.4 GB. This tool uses a concurrency limiter (4 simultaneous operations) to stay within safe memory bounds. Individual files exceeding ~100 MP may fail on mobile devices.

Each browser engine implements its own JPEG encoder with different quantization tables and Huffman coding strategies. Chromium uses libjpeg-turbo, Firefox uses its own fork, and Safari uses Apple's ImageIO framework. At Q = 85, file sizes can vary by 10-15% between browsers for the same source image. This is expected behavior and does not indicate a bug.

Yes. Despite the name, the Canvas API can decode any browser-supported image format (PNG, WebP, GIF, BMP, SVG rasterized) and re-encode to JPEG. Transparent regions in PNG/WebP will be composited against a white background before encoding, since JPEG does not support alpha channels.