Extremely Light-Weight Learning Based LDR to PQ HDR Conversion Using Bernstein Curves

Abstract

The paper proposes a novel automatic Low Dynamic Range (LDR) to Perceptual Quantizer (PQ) High Dynamic Range (HDR) system to convert a LDR input into a HDR output. The process is based on a machine learning model that generates a Bernstein inverse tone mapping (iTM) curve. The monotonic constrain is also considered to maintain the curve monotonic characteristic. The proposed model is kept very small and the iTM is implemented pixel by pixel so that the whole system is extremely light-weight. Experiment results show that the proposed iTM can learn the LDR to HDR conversion style of the experts and outperforms other methods.