HEIC vs JPG: Complete Format Comparison

JPG (also written as JPEG, for Joint Photographic Experts Group) is the most widely used image format in the world. Developed in 1992, JPG became the standard for digital photography and remains dominant more than three decades later.

JPG uses a lossy compression algorithm based on Discrete Cosine Transform (DCT). This approach is highly effective for photographs and images with smooth color transitions, achieving excellent compression ratios while maintaining visual quality. The "lossy" nature means some image data is discarded during compression, but at typical quality settings (80-95%), the loss is imperceptible to most viewers.

Why JPG Remains Dominant

• Universal Compatibility: Every device, operating system, browser, and application supports JPG
• Mature Ecosystem: 30+ years of optimization in software and hardware
• Predictable Behavior: Well-understood compression characteristics
• Web Standard: Native support in all web browsers since the beginning
• Industry Standard: Accepted by all print services, websites, and professional workflows
• No Licensing: JPG is royalty-free, unlike HEVC which requires licensing

JPG Limitations

JPG has limitations that newer formats address. It supports only 8-bit color depth, lacking the dynamic range of modern camera sensors. It cannot store transparency (alpha channels), requiring PNG for images with transparent backgrounds. JPG cannot contain multiple images or video clips like HEIC's Live Photo support. Each re-save of a JPG introduces additional compression artifacts, making it less ideal for repeated editing.

HEVC Compression (HEIC)

HEVC (H.265) represents a significant advancement over previous compression standards. It uses larger coding tree units (CTUs) of up to 64x64 pixels (compared to 16x16 macroblocks in older standards), enabling more efficient compression of high-resolution images. HEVC employs advanced prediction techniques, including 35 intra-prediction modes that better capture directional patterns in images.

The algorithm also uses improved entropy coding (CABAC) and sophisticated deblocking and sample adaptive offset (SAO) filters that reduce compression artifacts. These advancements combine to achieve roughly double the compression efficiency of JPG's DCT-based approach at equivalent quality levels.

DCT Compression (JPG)

JPG's Discrete Cosine Transform converts 8x8 pixel blocks into frequency coefficients. High-frequency components (fine details) can be more aggressively compressed because the human eye is less sensitive to them. This perceptual model made JPG revolutionary in 1992 and remains effective today.

However, the 8x8 block structure can create visible "blockiness" at high compression ratios. JPG also lacks the advanced prediction and filtering capabilities of HEVC, limiting its compression efficiency compared to modern formats.

Real-World File Size Comparison

A typical iPhone 14 Pro photo illustrates the difference:

• Original HEIC: 2.3 MB (12MP, highest quality)
• Converted to JPG at 95% quality: 4.8 MB
• Converted to JPG at 85% quality: 2.1 MB
• Converted to JPG at 75% quality: 1.2 MB

At equivalent file sizes, the HEIC typically shows better detail retention, especially in areas with subtle gradients like skies or skin tones. At 95% JPG quality (larger file), the visual difference becomes negligible for most purposes.