HEIC Quality and File Size: What You Need to Know

Introduction

One of the most common questions about the HEIC image format is how it manages to produce files that are significantly smaller than JPGs while maintaining the same or better visual quality. It sounds almost too good to be true, but the explanation lies in the advanced compression technology that underpins the format. In this article, we will explore exactly how HEIC achieves its impressive compression efficiency and what this means for your photos in practical terms.

The HEIC Advantage

HEIC files are typically 40% to 50% smaller than JPG files at equivalent visual quality. This is not a marginal improvement; it is a generational leap in compression efficiency. To put this in perspective, consider an iPhone with 64 GB of usable storage. Using JPG, you might fit around 15,000 photos. Using HEIC, that number jumps to roughly 25,000 to 30,000 photos. The visual quality of those photos is essentially indistinguishable.

This advantage is not the result of a single clever trick. It comes from a fundamentally more sophisticated compression architecture that improves on JPG's approach in nearly every dimension.

Understanding HEVC Compression

HEIC uses the HEVC (High Efficiency Video Coding) codec, also known as H.265, for image compression. HEVC was originally developed for video compression and represents the culmination of decades of research in signal processing and information theory. When applied to still images, it brings all of those advancements to bear on a single frame.

To understand why HEVC is so much more efficient than JPG's compression, we need to look at the specific technical improvements it introduces.

How HEIC Reduces File Size

Advanced Intra Prediction

When compressing an image, the codec tries to predict what each region of the image looks like based on surrounding regions. The better these predictions are, the less data needs to be stored to represent the actual image content.

JPG's predecessor in this regard uses a relatively simple prediction model. HEVC, by contrast, supports 35 different directional intra-prediction modes, allowing it to accurately predict pixel values along edges, gradients, and textures that run in virtually any direction. This means that smooth gradients in skies, subtle textures in fabric, and diagonal edges in architecture can all be represented with minimal residual data.

Larger Coding Tree Units

JPG divides an image into fixed 8x8 pixel blocks and compresses each block independently. This rigid block structure is one reason why heavily compressed JPGs show visible "blockiness." HEVC uses a flexible, hierarchical structure called Coding Tree Units (CTUs) that can range from 8x8 to 64x64 pixels.

In areas of an image with uniform content, such as a clear blue sky or a white wall, HEVC can use large 64x64 CTUs to represent the entire area very efficiently with minimal data. In areas with fine detail, such as text or intricate patterns, the codec subdivides into smaller blocks to preserve that detail. This adaptive approach is far more efficient than JPG's one-size-fits-all block strategy.

Better Entropy Coding

After the spatial prediction and transform steps, the resulting data must be further compressed using entropy coding, which is essentially a form of lossless data compression. JPG uses Huffman coding, a well-understood but relatively basic entropy coding method.

HEVC uses CABAC (Context-Adaptive Binary Arithmetic Coding), which is significantly more efficient. CABAC adapts its compression model based on the statistical patterns it observes in the data, squeezing out additional redundancy that Huffman coding leaves on the table. This improvement alone accounts for a meaningful portion of HEVC's size advantage over JPG.

Advanced Transform and Quantization

HEVC also improves on JPG's frequency-domain transform stage. While JPG uses only the 8x8 DCT (Discrete Cosine Transform), HEVC supports multiple transform sizes (4x4, 8x8, 16x16, 32x32) and can apply different transforms to different parts of the image. The quantization step, which controls the trade-off between quality and file size, is also more finely tuned in HEVC, allowing for better rate-distortion optimization.

Quality Comparison at the Same File Size

When you constrain both HEIC and JPG to the same file size and compare the resulting image quality, the difference is clearly visible, especially at lower file sizes. In controlled comparisons:

• At 500 KB (12 MP photo): JPG shows noticeable blocking artifacts, color banding in gradients, and loss of fine detail. HEIC at the same size retains significantly more detail and smoother color transitions.
• At 1 MB: JPG artifacts are less pronounced but still visible upon close inspection, particularly around sharp edges and in areas with subtle color variation. HEIC maintains cleaner edges and more accurate color reproduction.
• At 2 MB: Both formats look good at normal viewing distances, but pixel-level inspection reveals that HEIC preserves finer textures and produces fewer ringing artifacts around high-contrast edges.

Quality Comparison at the Same Quality

When you target the same perceived visual quality and compare the resulting file sizes, HEIC consistently produces smaller files:

• Excellent quality (nearly indistinguishable from original): A typical 12 MP photo might be 4 to 5 MB as JPG and 2 to 2.5 MB as HEIC
• Good quality (suitable for printing and detailed viewing): Approximately 2.5 to 3 MB as JPG and 1.2 to 1.5 MB as HEIC
• Acceptable quality (suitable for social media and screen viewing): Around 1.5 to 2 MB as JPG and 0.7 to 1 MB as HEIC

These numbers are approximate and vary depending on image content. Photos with lots of fine detail (like landscapes with foliage) tend to compress less efficiently in both formats than photos with large areas of smooth color.

Real-World Storage Savings on iPhone

Apple's decision to switch the iPhone's default photo format from JPG to HEIC was driven largely by storage considerations. Here are some real-world scenarios that illustrate the practical impact:

• Casual user (5,000 photos): Approximately 7.5 GB saved by using HEIC instead of JPG
• Active photographer (20,000 photos): Approximately 30 GB saved, which could be the difference between needing a 128 GB or 256 GB phone
• iCloud storage: HEIC reduces the amount of iCloud storage needed for photo backups, potentially saving money on monthly subscription costs
• Transfer times: Smaller files transfer faster over Wi-Fi and cellular networks, which matters when syncing photos to iCloud or sharing via AirDrop

Conversion Quality Considerations

When converting HEIC to JPG, there is an inherent quality trade-off because you are re-encoding an already-compressed image into a different lossy format. Each generation of lossy compression introduces additional quality loss. Here are some guidelines for choosing quality settings when converting:

Choosing Quality Settings

• Quality 95-100%: Minimal additional quality loss. Files will be larger than the original HEIC. Best for printing, archival, or professional editing.
• Quality 85-94%: Very slight quality loss that is imperceptible to most people in normal viewing conditions. A good default for general-purpose conversion.
• Quality 70-84%: Some quality loss may be visible upon close inspection. Suitable for web publishing and social media where smaller file sizes are prioritized.
• Quality below 70%: Noticeable quality degradation. Only use when file size constraints are severe.

When using OpenedFile's HEIC converter, you can select the quality level before conversion, giving you full control over the quality-size trade-off. For most uses, a quality setting of 90% provides an excellent balance.

When File Size Matters vs. Quality

Different situations call for different priorities:

Prioritize File Size When:

• Uploading to social media platforms that will re-compress the image anyway
• Sending photos via email where attachment size limits apply
• Publishing on websites where page load speed is critical
• Storing large photo libraries on devices with limited storage

Prioritize Quality When:

• Printing photos, especially at large sizes
• Professional photography and client deliverables
• Archiving important photos for long-term preservation
• Further editing or post-processing will be applied

In either case, keeping your originals in HEIC format is a smart strategy. The HEIC files serve as your highest-quality source, and you can convert to JPG at whatever quality level each specific use case requires.

Conclusion

HEIC's ability to produce files that are roughly half the size of JPGs without sacrificing visual quality is not magic; it is the result of decades of advancement in compression technology. From adaptive coding tree units and sophisticated intra prediction to CABAC entropy coding, every component of the HEVC codec represents a meaningful improvement over JPG's 1992-era compression architecture.

For everyday users, the practical takeaway is simple: HEIC lets you store more photos in less space without giving up quality. When you need to share those photos in a more compatible format, tools like OpenedFile's HEIC to JPG converter make the conversion quick and painless while letting you choose exactly the right quality level for your needs.