High-fidelity Image Compression for High-throughput and Energy-efficient Cameras

We propose a new encoder-friendly image compression strategy for high-throughput cameras and other scenarios of resource-constrained encoders. The encoder performs $\ell_{\infty}$-constrained predictive coding (DPCM coupled with uniform scalar quantizer), while the decoder solves an inverse problem of $\ell_{2}$ restoration of $\ell_{\infty}$ coded images. Although designed for minimum encoder complexity, the new codec outperforms the state-of-the-art encoder-centralized image codecs such as JPEG 2000 in PSNR for bit rates higher than 1.2 bpp, while maintaining much tighter $\ell_{\infty}$ error bounds as well. This is achieved through exploiting the tight error bound on each pixel naturally offered by the $\ell_{\infty}$-constrained encoder and by locally adaptive image modeling.