Color consistency in digital camera color reproduction based on machine learning

Abstract

Digital camera is the one of the main devices in the computer and multimedia technology and its color management model is the key to guarantee the color consistency in the succedent image production and transfers. The paper presents a color conversion model for digital camera based on BP neural network and the analysis of color rendering principle of digital camera. First, digital camera data is pretreated to a unitary field to satisfy the scope requirement of the input and output data of the BP model. Second, the color shade districts are taken to stand for the color space to decrease the calculation of the model. Third, the active item which can adjust BP model step dynamically is used to increase convergence speed of the BP model. Finally, the realization and experiment results show that, compared with some methods which is have relatively high accuracy, the algorithm can improve color conversion accuracy and can satisfy the engineering requirement in digital camera color management.