PNG to JPG Converter

Why Convert PNG to JPG

PNG to JPG conversion is one of the most popular image operations. The main reason is the dramatic file size reduction. A PNG image weighing 5-10 MB becomes a 300-800 KB file after conversion to JPG at 85% quality, while maintaining a visually identical appearance. For photographs and images with smooth color transitions, the size difference can be 10-15 times.

The PNG format (Portable Network Graphics) was created for tasks where pixel-perfect accuracy is critical: screenshots, diagrams, logos, images with text. The DEFLATE algorithm compresses data losslessly, guaranteeing byte-for-byte correspondence with the original. However, for photographs and complex images, this precision is excessive, and the file size is unjustifiably large.

JPG (JPEG) was designed specifically for photographs. The algorithm accounts for human vision characteristics: we distinguish brightness better than color nuances and perceive high-frequency details worse. By discarding information that the eye won't catch anyway, JPG achieves impressive compression while maintaining subjectively indistinguishable quality.

Technical Differences Between PNG and JPG Formats

Compression Algorithms and Their Impact on Quality

PNG uses a two-stage lossless compression algorithm. In the first stage, each row of pixels is processed by one of five filters (None, Sub, Up, Average, Paeth) that predict pixel values based on neighbors. Only deviations from predictions are recorded, which is especially effective for solid color areas. In the second stage, the DEFLATE algorithm (the same as in ZIP archives) compresses the filtered data by finding repeating sequences.

JPG applies lossy compression based on Discrete Cosine Transform (DCT). The image is converted from RGB to YCbCr color space (luminance + two chrominance components), then divided into 8×8 pixel blocks. Each block is transformed from spatial to frequency domain. Low-frequency components (overall tone, large gradients) are preserved accurately, high-frequency ones (fine details, textures) are rounded or discarded depending on quality level.

Comparison Table

Interesting fact: for images with few colors and sharp boundaries (icons, pixel art, simple graphics), PNG can be more compact than JPG. This is because DEFLATE efficiently compresses repeating patterns, while DCT introduces artifacts in areas with sharp transitions.

Handling Transparency During Conversion

PNG supports a full alpha channel with 256 transparency levels. This allows creating smooth semi-transparent shadows, blurred edges, glass effects. JPG has no alpha channel — the format only supports fully opaque images.

When converting PNG with transparency to JPG, you need to determine what fills the transparent areas. The standard solution is a white background, which works with most designs. However, for images intended for dark backgrounds, a white fill will create a visible outline. In such cases, either choose an appropriate fill color or keep the PNG.

Semi-transparent pixels (alpha 1-254) are converted using alpha compositing: the resulting pixel color is calculated as a blend of the source color and background color proportional to transparency. Formula: Result = Source × Alpha + Background × (1 - Alpha).

Practical PNG to JPG Conversion Scenarios

Image Optimization for Websites

Loading speed directly affects conversion rates and search rankings. Google considers Core Web Vitals, where LCP (Largest Contentful Paint) critically depends on image size. Converting PNG photos to JPG can speed up page loading several times.

A typical webmaster task: receive a layout from a designer with all elements in PNG, determine which can be safely converted to JPG. The rule is simple:

• Keep PNG: logos, icons, elements with transparency, interface screenshots, images with text
• Convert to JPG: photos, banners with photo backgrounds, background images without transparency

For e-commerce stores with thousands of product photos, PNG to JPG conversion saves terabytes of traffic and improves user experience.

Preparing Images for Email Campaigns

Email marketing requires balancing image quality and message size. Email clients limit attachment weight (usually 10-25 MB), and heavy emails more often end up in spam. Images in the email body must load instantly, or the recipient will close it without waiting.

Email recommendations:

• Total image weight in email: no more than 500 KB
• Individual image: 50-150 KB
• JPG quality: 70-80% (sufficient for screen viewing)

PNG in email is justified only for company logos with transparent backgrounds or icons.

Publishing on Social Media

Social networks automatically recompress uploaded images, but the source format affects the result. Uploading heavy PNG takes more time and can cause timeouts on mobile internet. Most platforms are optimized for JPG:

When uploading photos, converting PNG→JPG before publishing gives you control over compression quality instead of trusting platform algorithms.

Sending Images via Messengers

Messengers aggressively compress images to save traffic. WhatsApp reduces quality to a level where text in screenshots becomes unreadable. Telegram in "normal" mode also recompresses photos.

Paradoxically, pre-converting PNG to JPG with controlled quality can yield better results:

1. You set quality to 85-90% — sufficient for viewing
2. The file is already compact, messenger applies less additional compression
3. Final quality is higher than when uploading heavy PNG

For sending without compression: in Telegram send the file as a document, in WhatsApp use file manager transfer.

Uploading to Marketplaces and Classifieds

Amazon, eBay, Etsy and other platforms have format and size requirements for product images. Most prefer JPG:

• Amazon: JPG preferred; minimum 1000×1000, recommended 2000×2000
• eBay: JPG; maximum 12 MB; recommended 1600×1600
• Etsy: JPG, PNG; minimum 2000px on longest side

Converting PNG product photos to JPG speeds up uploading, reduces storage space on the platform, and ensures correct thumbnail display in catalogs.

Quality Settings During Conversion

JPG Quality Scale and Its Impact

The JPG quality parameter (1-100%) determines the degree of DCT coefficient quantization:

• 100%: minimal quantization, file size close to PNG, virtually no artifacts
• 90-95%: slight compression, artifacts invisible even when zoomed, optimal for printing
• 80-90%: moderate compression, artifacts visible only at 200%+ zoom, web standard
• 70-80%: noticeable compression, slight artifacts on gradients, sufficient for previews
• 50-70%: strong compression, visible artifacts around contrasting edges
• Below 50%: pronounced block artifacts, only suitable for thumbnails

The relationship between file size and quality is non-linear. Going from 100% to 90% reduces the file by 2-3 times, while 90% to 80% — only by 20-30%. The optimal point for most tasks is 82-88%.

Quality Recommendations

Content Impact on Optimal Quality

Image type affects artifact visibility:

Nature photos, portraits: textures of foliage, skin, fabric mask artifacts. You can safely use 80-85%.

Architecture, technical photos: straight lines and solid surfaces reveal blockiness. Recommended 88-92%.

Gradients, sky, blurred backgrounds: banding artifacts are noticeable on smooth transitions. Need 90-95%.

Graphics with text: sharp letter boundaries create characteristic "halos" during compression. Better 92-95% or keep PNG.

Conversion Process: Technical Details

PNG to JPG Transformation Steps

1. Reading PNG file: decoder decompresses DEFLATE data, applies reverse filters to restore pixel values. If PNG contains alpha channel, four components (RGBA) are extracted.

2. Alpha channel processing: for pixels with partial or full transparency, alpha compositing with background color is performed. Result — fully opaque RGB image.

3. Applying user settings: scaling, rotation, flipping, grayscale conversion — performed at this stage on uncompressed data.

4. Color space conversion: image is converted from RGB to YCbCr. Luminance channel (Y) maintains full resolution, chrominance (Cb, Cr) are usually subsampled 4:2:0 (halved on each axis).

5. Discrete Cosine Transform: each 8×8 pixel block is transformed into a frequency coefficient matrix. Top-left element (DC) — block's average brightness, others (AC) — details of varying frequency.

6. Quantization: coefficients are divided by values from quantization table depending on quality parameter. High-frequency coefficients are zeroed first.

7. Entropy coding: quantized coefficients are compressed using Huffman or arithmetic coding.

8. File formation: JPG markers, quantization and Huffman tables, compressed data are written.

Chroma Subsampling

The human eye has 5 times more brightness receptors than color receptors. This allows storing color information at lower resolution without noticeable quality loss. Subsampling schemes:

• 4:4:4: no subsampling, maximum color quality, larger size
• 4:2:2: color halved horizontally, rarely used
• 4:2:0: color halved on both axes, standard for most JPG

For images with fine colored details (charts, diagrams), 4:2:0 subsampling can cause color halos. In such cases, keeping PNG is better.

Alternative Formats for Size Reduction

WebP as a Modern Alternative

Google's WebP offers the best of both worlds: lossy compression 25-35% more efficient than JPG, lossless compression 25% more efficient than PNG, while supporting transparency.

If your target audience uses modern browsers, WebP is the optimal choice. For maximum compatibility, JPG remains the standard.

AVIF — Format of the Future

AVIF is based on the AV1 video codec and provides 40-50% more efficient compression than JPG. Supports HDR, wide color gamut, transparency. Main drawback — slow encoding and incomplete browser/software support.

For critical projects, a progressive enhancement strategy is recommended: AVIF → WebP → JPG via <picture> tag.

Batch Conversion of Multiple Files

When working with large image collections, manual conversion is inefficient. Typical batch processing scenarios:

• Screenshot archive: converting a folder of PNG screenshots to JPG to reduce backup size
• Photo gallery: preparing an album for social media publication
• Product photos: processing images for marketplace upload
• Documentation: converting screenshots for technical manuals

Batch conversion maintains consistent quality settings for all files, guaranteeing uniform results.

Working with Different PNG Types

PNG-8 vs PNG-24/32

PNG-8 uses an indexed palette of up to 256 colors. Files are compact but color range is limited. When converting to JPG, the image is automatically expanded to full color.

PNG-24 stores 16.7 million colors (24 bits), same as JPG. Conversion is straightforward, main savings come from lossy compression.

PNG-32 adds an 8-bit alpha channel to PNG-24. During conversion, transparency requires processing — filling with background color.

Interlaced PNG

Interlaced PNGs contain image data in an order that allows displaying a blurry preview during loading. This doesn't affect conversion quality — the decoder restores the full image before processing anyway.

When NOT to Convert PNG to JPG

Images with Text and Thin Lines

JPG artifacts are especially noticeable at boundaries of contrasting areas. Letters, diagrams, drawings acquire characteristic "halos" and blurring after conversion. Even at 95% quality, the result is worse than the original PNG.

Pixel Art and Icons

Images with limited palettes and sharp boundaries are more efficiently stored in PNG-8. When converting to JPG:

• Sharp pixel boundaries become blurred
• Colors are distorted due to subsampling
• File size may even increase

Images for Multiple Editing Sessions

If a file will be repeatedly opened, edited, and saved, each JPG save introduces additional losses. PNG as an intermediate format preserves quality between iterations.

Graphics with Transparency

Obvious but important: if transparency is necessary for final use (overlay on other images, placement on colored background), JPG conversion is impossible without losing this functionality.