Representing Images in 200 Bytes: Compression via Triangulation
This addresses the problem of improving thumbnail compression for mobile web responsiveness, representing an incremental advance over existing codecs.
The paper tackles extreme image compression for mobile bandwidth constraints by proposing a novel adaptive triangulation method and encoding algorithm, achieving better PSNR and SSIM than JPEG and WebP at sizes around 200 bytes.
A rapidly increasing portion of internet traffic is dominated by requests from mobile devices with limited and metered bandwidth constraints. To satisfy these requests, it has become standard practice for websites to transmit small and extremely compressed image previews as part of the initial page load process to improve responsiveness. Increasing thumbnail compression beyond the capabilities of existing codecs is therefore an active research direction. In this work, we concentrate on extreme compression rates, where the size of the image is typically 200 bytes or less. First, we propose a novel approach for image compression that, unlike commonly used methods, does not rely on block-based statistics. We use an approach based on an adaptive triangulation of the target image, devoting more triangles to high entropy regions of the image. Second, we present a novel algorithm for encoding the triangles. The results show favorable statistics, in terms of PSNR and SSIM, over both the JPEG and the WebP standards.