Native AVIF Hardware Pipelines in Mobile Chips

As modern smartphones transition away from legacy JPEG compression toward more efficient image formats, mobile system-on-chips (SoCs) are adapting their processing architectures. This article analyzes whether dedicated hardware image signal processors (ISPs) in mobile silicon will incorporate native AVIF (AV1 Image File Format) hardware pipelines, evaluating current architectural trends, the role of AV1 video hardware, and the technical hurdles required to achieve zero-latency AVIF capture.

The Push for AVIF in Mobile Devices

The AV1 Image File Format (AVIF) offers significant improvements over legacy formats like JPEG and even HEIC. Developed by the Alliance for Open Media (AOMedia), AVIF delivers superior compression efficiency, native support for 10-bit and 12-bit color depths, high dynamic range (HDR), and a wide color gamut (WCG)—all under an open-source, royalty-free license.

Because modern smartphone camera sensors capture high dynamic range data natively, standard 8-bit JPEG compression discards vast amounts of image fidelity. While HEIC addressed this for some ecosystems, its complex licensing structure has hindered universal adoption across the web and operating systems. AVIF provides an open alternative, making native mobile support a priority for device manufacturers and platform developers.

Current Mobile SoC Architecture: ISP vs. Codec

In modern mobile SoCs—such as Qualcomm’s Snapdragon series, Apple’s A-series, and MediaTek’s Dimensity line—image capture relies on a specialized hardware pipeline.

1. The ISP (Image Signal Processor): Operates on raw sensor data, performing demosaicing, noise reduction, white balance adjustment, and tone mapping.
2. Dedicated Image Encoders: Historically, chips included dedicated fixed-function JPEG encoders connected directly to the ISP output to serialize raw frames into compressed files instantaneously.
3. Video Processing Units (VPUs): Handle video encoding and decoding (such as H.264, HEVC, and AV1) separate from the ISP.

Because AVIF uses intra-frame compression derived directly from the AV1 video standard, encoding an AVIF file is essentially encoding a single keyframe of AV1 video wrapped in an HEIF/ISOBMFF container.

Will Mobile ISPs Include Native AVIF Pipelines?

Yes, dedicated hardware support for AVIF is actively arriving in mobile silicon, though the architectural execution differs from legacy JPEG pipelines.

Rather than building a completely separate fixed-function AVIF block within the ISP, chipmakers are implementing native AVIF pipelines through two primary approaches:

1. Tight Coupling of the ISP and Hardware AV1 Encoders

Modern flagship chipsets are integrating AV1 hardware encoders into their media engines. To enable seamless AVIF still capture, chipmakers are establishing direct memory-to-memory hardware paths between the ISP and the AV1 encoder. This pipeline allows full-resolution sensor bursts to stream directly into the AV1 intra-frame encoding block without relying on high-latency software processing by the CPU or GPU.

2. Multi-Format Image Compression Hardware

Silicon designers are updating the traditional fixed-function "JPEG engines" into universal still-image hardware encoders. These modular accelerators support JPEG, HEIC, and AVIF natively in silicon. This design enables smartphones to capture multi-frame HDR photos and compress them directly into AVIF with near-zero latency and minimal thermal penalty.

Key Drivers and Challenges

Drivers

• Burst-Mode Performance: Software-based AV1 intra-encoding is computationally intensive. Hardware pipelines are required to sustain the high frame rates needed for burst photography and zero-shutter-lag operations.
• HDR Standards Alignment: As platforms like Android adopt Ultra HDR and ISO-compliant gain maps, AVIF provides the native 10-bit infrastructure required to store these images efficiently.
• Web Ecosystem Alignment: Major web browsers already support AVIF. Native capture pipelines ensure that mobile uploads are immediately web-ready without server-side transcoding.

Challenges

• Silicon Area Constraints: AV1 encoding algorithms are more complex than JPEG or HEVC, requiring more transistors. Allocating dedicated silicon space for AVIF intra-encoding requires balancing power and area budgets against other accelerator blocks.
• Encoder Tuning: Tuning an AV1 encoder for still images requires distinct spatial quality optimizations compared to temporal video encoding. Chipmakers must ensure that their hardware encoders prioritize spatial detail over motion-optimized trade-offs.

Conclusion

The integration of native AVIF hardware pipelines in mobile SoCs is a technical inevitability. Leading silicon vendors have already transitioned from software decode/encode paths to hardware-accelerated AV1 infrastructure. Over upcoming processor generations, direct hardware pathways between the camera ISP and AV1 intra-frame encoding engines will become standard, establishing AVIF alongside JPEG as a default native capture format on mobile devices.