Calculating Color Differences of Images via Siamese Neural Network

Recently, the color difference (CD) of standard dynamic range (SDR) images has attracted the attention of researchers. It is worth noting that due to the development of high dynamic range (HDR) image generation technology, the CD of the SDR and HDR images is also worth in-depth research. This is because the HDR image generated from an original SDR image may have changes in color. Some color changes can give people a comfortable impression, but this may also change the information originally expressed in the SDR image. Therefore, this paper researches the CD of the original SDR image and the generated HDR image, and proposes a network to predict the CDs of SDR and HDR image pairs. Specifically, we first build a SDR-HDR image CD dataset. The dataset contains 504 SDR and HDR image pairs, where HDR images are generated from the SDR images using five HDR image generation methods. Second, we propose a siamese neural network to predict the CDs of SDR and HDR image pairs, which consists of three parts: space conversion, feature extraction, and CD calculation. Finally, experiments prove that the proposed network has a superior ability to predict the CDs of SDR and HDR image pairs.