In this paper, we propose a coding method for camera raw images with high dynamic ranges. Our encoder has two layers. In the first layer, 24 bit low dynamic range image is encoded by a conventional codec, and then the residual image that represents the difference between the raw image and its approximation is encoded in the second layer. The approximation is derived by a polynomial fitting. The main advantage of this approach is that applying the polynomial model reduces the correlation between the raw and 24 bit images, which increases coding efficiency. Experiments shows compression efficiency is significantly improved by taking an inverse tone mapping into account.

In this paper, we propose a coding algorithm for High Dynamic Range Images (HDRI). Our encoder applies a tone mapping model based on scaled µ-Law encoding, followed by a conventional Low Dynamic Range Image (LDRI) encoder. The tone mapping model is designed to minimize the difference between the tone-mapped HDRI and its LDR version. By virtue of the nature of the µ-Law model, not only the quality of the HDRI but also the one of the LDRI is improved, compared with a state of the art in conventional HDRI coding methods. Furthermore the error limit caused by our encoding is theoretically analyzed.