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.